Abstract

An example of a method of automated slide image focus evaluation includes receiving an image scan of a histological slide, segmenting the image scan into a plurality of regions, generating a focus score for each region of the plurality of regions using a trained computer-implemented machine-learning model, determining a number of regions of the plurality of regions having focus scores that satisfy a threshold focus score, generating a determination of whether the image scan is acceptable for diagnostic use based on whether the number of regions satisfies a threshold number of regions, and generating an indication of the determination of whether the image scan is acceptable for diagnostic use. The trained computer-implemented machine-learning mode is configured to accept image data as an input and to output a value describing an extent to which the image data is in focus.

IPC Classes  ?

• G02B 21/24 - Base structure
• G06T 7/00 - Image analysis

Abstract

A method of labeling data for training a machine-learning model includes capturing a set of z-stacked images of a slide containing tissue, segmenting the set of z-stacked images to generate a set of image regions, generating a plurality of sharpness scores by generating a sharpness score for each image region of the set of image regions, identifying a highest sharpness score of the plurality of sharpness scores, generating a plurality of normalized sharpness scores by normalizing each sharpness score of the plurality of sharpness scores to the highest sharpness score, and generating labeled data by labeling each image region of the set of image regions with a respective normalized sharpness score of the plurality of normalized sharpness scores representing relative sharpness of the image region. Each image of the set of z-stacked images is captured at a different distance between a lens and the slide.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• G02B 21/24 - Base structure

Abstract

A method for automated intelligent quality control may be provided. Such a method may comprise applying a quality control process to a plurality of histological images. Such a quality control process may comprise, for each of a set of artifacts, determining whether a histological image to which the quality control process is applied features that artifact. Such a quality control process may also comprise, for each artifact from the set of artifacts, based on determining that that histological image to which the quality control process is applied features that artifact, determining whether to generate a flag indicating that the histological image to which the quality control process is applied features that artifact.

IPC Classes  ?

• G02B 21/24 - Base structure
• G06T 7/00 - Image analysis
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

Image scanning can be accelerated using a method for generating upsampled images. Such a method may comprise establishing relative motion between a field of view of a camera and a sample supported by a scanning stage in a first dimension at a compressing scanning speed, capturing an input image, and generating an upsampled image based on applying an upsampling algorithm to the input image. In some cases, the compressing scanning speed may be a speed that is greater than a synchronized scanning speed, wherein the synchronized scanning speed is synchronized with a line rate of the camera.

IPC Classes  ?

• G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
• G06T 5/73 - DeblurringSharpening

Goods & Services

Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for tracking the location of histological and cytological specimens; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology. Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology.

Goods & Services

Downloadable and recorded computer operating software for image analysis and image storage devices; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for tracking the location of histological and cytological specimens; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology. Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology.

Abstract

Subpixel line scanning. A slide scanning device comprises a plurality of line sensors, each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an upsampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/26 - StagesAdjusting means therefor
• H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
• H04N 25/701 - Line sensors

Abstract

An apparatus configured for use with a user interface to manipulate at least one digital while slide image (WSI) displayed on the user interface includes a body, a first control knob, and a second control knob. The first control knob extends from a side of the body and is configured to rotate to control a first manipulation of the digital WSI on the user interface. The second control knob extends from an opposite side of the body and is configured to rotate to control a second manipulation of the digital WSI on the user interface. The first manipulation is different from the second manipulation. At least one of the first control knob or the second control knob is configured to translate to control one or more user interface navigation features associated with the user interface.

IPC Classes  ?

• G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
• G06F 3/0362 - Pointing devices displaced or positioned by the userAccessories therefor with detection of 1D translations or rotations of an operating part of the device, e.g. scroll wheels, sliders, knobs, rollers or belts
• G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• G06F 3/04855 - Interaction with scrollbars
• G16H 10/00 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data

Goods & Services

Automated digital scanning system comprised of computer hardware and recorded and downloadable software for optical microscopy, motorized sample positioning, digital image capture, and data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical environments; image analysis devices, namely, image scanners and optical scanners; scanners for whole slide imaging, for scientific or research purposes; electronic image recording, image storing and image representing devices, namely, digital cameras; recorded and downloadable computer operating software for use with image analysis and image data storage devices; recorded and downloadable operating software for automated digital slide scanning systems; recorded and downloadable computer software for digitizing microscope slides, viewing images of the slides, integrating slide images with other data, and managing and analyzing slide images and associated data, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; recorded and downloadable digital slide information management software, namely, software for digitizing glass microscope slides into diagnostic quality images and for displaying the slide images in context with reports, case histories and other associated documents or data that are optionally cross-linked and concurrently viewable, all for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; recorded and downloadable software for tracking the location of histological and cytological specimens; recorded and downloadable computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Diagnostic apparatus for medical purposes, namely, digital pathology slide scanners for medical diagnostic uses; scanners for whole slide imaging for medical diagnostic uses; medical apparatus and instruments, namely, digital pathology slide imaging and processing systems for medical and clinical diagnostic purposes comprised of microscopes, digital cameras, digital slide scanners, and computer hardware for digital image capture and data processing

Goods & Services

(1) Downloadable and recorded computer operating software for image analysis and image storage devices; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for tracking the location of histological and cytological specimens; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology. (2) Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology.

Goods & Services

(1) Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for tracking the location of histological and cytological specimens; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology. (2) Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology.

Goods & Services

Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens. Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer software; design and development of computer software.

Abstract

It is possible to digitize a sample using a scanning in a manner which automatically accounts for tilt which may otherwise result in some or all of a digitized image being out of focus. This may be done by obtaining a plurality of segments of image data and combining the plurality of segments of image data into a contiguous digital image of the sample. In this type of scenario, obtaining the plurality of segments of image data may comprise capturing one or more segments using an initial segment width, detecting tilted image data and, based on detecting the tilted image data, determining a narrower segment width and capturing one or more segments using the narrower segment width.

IPC Classes  ?

• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Goods & Services

(1) Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens. (1) Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer software; design and development of computer software.

Goods & Services

Downloadable and recorded middleware software; downloadable and recorded middleware software in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens. Software as a service (SaaS) services featuring middleware software; software as a service (SaaS) services featuring middleware software in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer middleware software; design and development of computer middleware software.

Abstract

An apparatus for interacting with one or more digital whole slide images (WSIs) acquired by an imaging device includes a display, a memory, and one or more hardware processors. The memory' is configured to store computer-executable instructions. The one or more hardware processors are in communication with the display and the memory. The one or more hardware processors are configured to drive the display using the computer-executable instructions of the memory'- such that the one or more hardware processors are configured to generate a. user interface. The user interface includes an image layer and one or more mask layers overlaying the image layer. The one or more mask layers have a predetermined opacity level. The one or more hardware processors are further configured to automatically adjust the predetermined opacity level as a function of a magnification level of the image layer.

IPC Classes  ?

• G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
• G06T 7/00 - Image analysis
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Goods & Services

Automated digital scanning system comprised of computer hardware and recorded and downloadable software for optical microscopy, motorized sample positioning, digital image capture, and data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical environments; image analysis devices, namely, image scanners and optical scanners; scanners for whole slide imaging, for scientific or research purposes; electronic image recording, image storing and image representing devices, namely, digital cameras; recorded and downloadable computer operating software for use with image analysis and image data storage devices; recorded and downloadable operating software for automated digital slide scanning systems; recorded and downloadable computer software for digitizing microscope slides, viewing images of the slides, integrating slide images with other data, and managing and analyzing slide images and associated data, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; recorded and downloadable digital slide information management software, namely, software for digitizing glass microscope slides into diagnostic quality images and for displaying the slide images in context with reports, case histories and other associated documents or data that are optionally cross-linked and concurrently viewable, all for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; recorded and downloadable software for tracking the location of histological and cytological specimens; recorded and downloadable computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Diagnostic apparatus for medical purposes, namely, digital pathology slide scanners for medical diagnostic uses; scanners for whole slide imaging for medical diagnostic uses; medical apparatus and instruments, namely, digital pathology slide imaging and processing systems for medical and clinical diagnostic purposes comprised of microscopes, digital cameras, digital slide scanners, and computer hardware for digital image capture and data processing

Goods & Services

(1) Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimen. (1) Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer middleware software; design and development of computer middleware software.

Abstract

Systems and methods for classification of histopathology images are disclosed. In one aspect, an apparatus for detecting a medical condition in a histopathology image includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of patches at a plurality of magnification levels from the histopathology image, apply a deep learning algorithm to each of the patches, extract, from applying the deep learning algorithm, information representative of a hierarchical relationship that links characteristics of the histopathology image present at one level and another level of the plurality of magnification levels, and identify the medical condition based on the extracted information representative of the hierarchical relationship for characteristics present at the one level and at the another level of the plurality of magnification levels.

IPC Classes  ?

• G06T 7/00 - Image analysis

Goods & Services

Downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded software for tracking the location of histological and cytological specimens; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations , all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; medical diagnostic apparatus for the analysis of biological samples

Goods & Services

Downloadable and recorded computer operating software for image analysis and image storage devices; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for tracking the location of histological and cytological specimens; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology

Goods & Services

Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for tracking the location of histological and cytological specimens; Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use

Goods & Services

Automated image analysis computer hardware system comprising printed circuit boards, hard and floppy disk drives, keyboard, monitors, printer, plotter, digital scanner, video camera and camera stand; computer software for cellular image and chromosome analysis in the field of molecular biology and genetic research.

Goods & Services

Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; Downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; Downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; Downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; Software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; Installation, repair and maintenance of computer software; Design and development of computer software

Goods & Services

Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; Downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; Downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; Downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; Software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; Installation, repair and maintenance of computer middleware software; Design and development of computer middleware software

Abstract

Mitosis can be detected using a two step detection method. This type of a detection method may comprise, obtaining a detection output by applying a detection model to the tissue image. Subsequently, for each nucleus in a set of nuclei identified as undergoing mitosis in the detection output, making a certainty determination for that nucleus. Then, for each nucleus from a subset of nuclei, a classification model may be applied to that nucleus based on a relationship between a confidence for that nucleus and a first threshold. An output may then be provided which identifies each nucleus identified in the detection output as undergoing mitosis and for which the confidence is above the first threshold as undergoing mitosis. Additionally, the output may identify each nucleus from the subset of nuclei indicated as undergoing mitosis in the classification result obtained for that nucleus as undergoing mitosis.

IPC Classes  ?

• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts

Abstract

A machine learning model can be trained to add markings to representations of nuclei undergoing mitosis on tissue images. This may include performing a set of training data creation steps, and a set of model training steps. The training data creation steps may include receiving a tissue image comprising a set of representation of nuclei undergoing mitosis, and creating a target image corresponding to the tissue image. The set of model training steps may include providing the tissue image to a generator model, generating an output image based on the tissue image using the generator model, and training the generator model to create improved output images based on differences between the output image and the target image.

IPC Classes  ?

• G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.

Goods & Services

Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.

Abstract

A digital pathology scanning apparatus is configured to initiate a rescan of a portion of a sample responsive to detecting a mechanical vibration during image acquisition that exceeds a predetermined threshold. The digital pathology scanning apparatus includes a plurality of sensors and a processor that analyzes sensor data received during movement of a scanning stage supporting a sample during image acquisition. The processor is configured to identify a mechanical vibration imparted on the scanning stage during image acquisition and determine if the mechanical vibration exceeds a predetermined threshold. If the predetermined threshold is exceeded, the processor is configured to initiate a rescan of the portion of the sample being scanned at the time of the mechanical vibration.

IPC Classes  ?

• H04N 23/68 - Control of cameras or camera modules for stable pick-up of the scene, e.g. compensating for camera body vibrations
• G01P 13/00 - Indicating or recording presence or absence of movementIndicating or recording of direction of movement
• G02B 21/00 - Microscopes
• H04N 3/02 - Scanning details of television systemsCombination thereof with generation of supply voltages by optical-mechanical means only
• H04N 23/67 - Focus control based on electronic image sensor signals
• H04N 25/711 - Time delay and integration [TDI] registersTDI shift registers

Goods & Services

Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all of the foregoing not for medical use apart from medical research; image analysis devices, namely, scanners for capturing images for analysis for use in medical research and clinical laboratory environments, all of the foregoing not for medical use apart from medical research; electronic image recording, image storing and image representing devices, namely, digital cameras; Downloadable and recorded computer operating software for image analysis and image storage devices; Downloadable and recorded computer operating software for automated digital scanning systems; Downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; Downloadable and recorded computer software for tracking the location of histological and cytological specimens; Downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology

Abstract

Methods and systems method for determining quality of an image after a system configuration change. A method includes receiving an indication of a configuration update of an imaging system, processing a test image using the image display system to generate updated test image pixel data for display on the imaging system, determining if the updated test image pixel data is different than the ground truth pixel data of the test image by more than a quality threshold, and in response to the updated test image pixel data being different than the ground truth pixel data of the test image by more than the quality threshold, generate in indicator that the configuration change adversely affected the image generation properties of the imaging system.

IPC Classes  ?

• G06T 7/00 - Image analysis

Abstract

A computer apparatus and method for identifying and visualizing tumors in a histological image and measuring a tumor margin are provided. A CNN is used to classify pixels in the image according to whether they are determined to relate to nontumorous tissue, or one or more classes for tumorous tissue. Segmentation is carried out based on the CNN results to generate a mask that marks areas occupied by individual tumors. Summary statistics for each tumor are computed and supplied to a filter which edits the segmentation mask by filtering out tumors deemed to be insignificant. Optionally, the tumors that pass the filter may be ranked according to the summary statistics, for example in order of clinical relevance or by a sensible order of review for a pathologist. A visualization application can then display the histological image having regard to the segmentation mask, summary statistics and/or ranking. Tumor masses extracted by resection are painted with an ink to highlight its surface region. The CNN is trained to distinguish ink and no-ink tissue as well as tumor and no-tumor tissue. The CNN is applied to the histological image to generate an output image whose pixels are assigned to the tissue classes. Tumor margin status of the tissue section is determined by the presence or absence of tumor-and-ink classified pixels. Tumor margin involvement and tumor margin distance are determined by computing additional parameters based on classification-specified inter-pixel distance parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
• G06F 18/24 - Classification techniques
• G06N 3/08 - Learning methods
• G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G06F 3/04842 - Selection of displayed objects or displayed text elements

Abstract

Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to 500 an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.

IPC Classes  ?

• H04N 23/67 - Focus control based on electronic image sensor signals
• G02B 21/00 - Microscopes
• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• H04N 3/06 - Scanning details of television systemsCombination thereof with generation of supply voltages by optical-mechanical means only having a moving lens or other refractor
• H04N 23/90 - Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

Abstract

Features are disclosed for training a machine learning model to identify objects in histological images. A system may obtain an image and determine a number of objects in the image. For example, the system may determine a percentage of objects in the image with a particular object type. Further, the system may determine a weight. The weight may specify a percentage of the image occupied by objects with the particular object type. The system can generate training set data that includes the image, data identifying the number of objects in the image, and the weight. The system can use the training set data to train a machine learning model to predict a number of objects in a different image and a weight. The system can implement the machine learning model based on training the machine learning model.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Features are disclosed for rendering an image using a GPU and CPU based rendering pipeline. An imaging system may include a GPU and a CPU that each include a portion of an image renderer. A component of the GPU can process the set of image tiles to generate a texture with a wrapped tile coordinate. A component of the GPU can further store the image data as a level of a texture pyramid. As subsequent image data is received, a component of the GPU can access the texture pyramid to determine previously stored image tiles. A component of the GPU can use the previously stored image tiles in rendering the subsequent image data.

IPC Classes  ?

• G06T 1/20 - Processor architecturesProcessor configuration, e.g. pipelining
• G06T 11/00 - 2D [Two Dimensional] image generation
• G06T 1/60 - Memory management
• G06T 9/00 - Image coding

Abstract

Systems and methods for normalizing image data obtained using multispectral imaging are disclosed. In one aspect, an image analysis apparatus includes an imaging device configured to perform a multispectral scan of a tissue sample to generate image data, a processor, and at least one computer-readable memory. The processor is configured to receive the image data from the imaging device and preprocess the image data to generate a normalization factor based on pixel values of the image data within at least one sub-region of the image data. The processor is also configured to provide the preprocessed image data and the normalization factor as inputs to a machine learning algorithm and determine, based on an output of the machine learning algorithm, whether the image data is indicative of a disease present in the tissue sample.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Features are disclosed for imaging block and slice samples using an imaging system. The imaging system can link the images by identifiers associated with the block and slice samples. The imaging system can train a machine learning algorithm based on correctly linked images. In some embodiments, the trained machine learning algorithm may include an image analysis module or a convolutional neural network. The imaging system can use the trained machine learning algorithm in order to determine a confidence score of a match between the block and the slice samples. The trained machine learning algorithm can use features of the block and the slice samples such as shape and tissue morphology to determine whether the samples match. In some embodiments, when the confidence score is below a certain threshold, the imaging system can alert a user that the samples may not match.

IPC Classes  ?

• G06T 7/00 - Image analysis

Abstract

An input device allows a user to manipulate an image displayed by a user interface (UI) of a computer. The input device includes a housing, a first rotatable control knob supported by the housing, and a second rotatable control knob supported by the housing. The first and second rotatable control knobs allow the user to perform at least zooming and panning manipulations of the image on the UI. The input device can further include a third rotatable control knob and a touch pad. The input device can be configured as a keyboard.

IPC Classes  ?

• G06F 3/0362 - Pointing devices displaced or positioned by the userAccessories therefor with detection of 1D translations or rotations of an operating part of the device, e.g. scroll wheels, sliders, knobs, rollers or belts
• G06F 3/02 - Input arrangements using manually operated switches, e.g. using keyboards or dials
• G06F 3/0354 - Pointing devices displaced or positioned by the userAccessories therefor with detection of 2D relative movements between the device, or an operating part thereof, and a plane or surface, e.g. 2D mice, trackballs, pens or pucks
• G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour

Abstract

An apparatus and methods for determining features in an image of a Hematoxylin and Eosin (H&E) stained tissue sample. An apparatus can be configured to apply a machine learning model to the H&E stained tissue sample image to determine features in the image. Applying the machine learning model can include performing convolution operations on the H&E stained tissue sample image to generate a plurality of initial feature maps, applying octave-convolution-first-layer operations on the initial feature maps to generate initial high-frequency feature maps and low-frequency feature maps, applying octave-convolution operations on the high-frequency initial feature maps to generate refined high-frequency feature maps, applying octave-convolution operations on the low-frequency initial feature maps to generate refined low-frequency feature maps, and applying octave-convolution last layer operations on the refined high-frequency feature maps and the refined low-frequency feature maps to produce combined feature maps.

IPC Classes  ?

• G06V 10/771 - Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
• G06T 7/00 - Image analysis
• G06T 7/12 - Edge-based segmentation
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

Abstract

Systems and methods for classification of histopathology images arc disclosed. In one aspect, an apparatus for detecting a medical condition in a histopathology image includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of patches at a plurality of magnification levels from the histopathology image, apply a deep learning algorithm to each of the patches, extract, from applying the deep learning algorithm, information representative of a hierarchical relationship that links characteristics of the histopathology image present at one level and another level of the plurality of magnification levels, and identify the medical condition based on the extracted information representative of the hierarchical relationship for characteristics present at the one level and at the another level of the plurality of magnification levels.

IPC Classes  ?

• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
• G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
• G06N 3/045 - Combinations of networks
• G06F 18/25 - Fusion techniques

Abstract

Systems and methods for determining pixel classification information using images depicting at least a portion of a whole slide image (WSI) of a stained tissue sample. A system can store a first image of the tissue sample at a first resolution, a second image of the tissue sample at a second resolution that is higher than the first resolution, and a third image of the tissue sample at a third resolution that is higher than the second resolution, the first, second, and third images depicting at least a portion of a same area of the tissue sample. The system can include be configured to generate first feature information based on the first image, generate second feature information based on the second image, and determine pixel classification information of at least a portion of the WSI based on the third image, the first feature information and second feature information.

IPC Classes  ?

• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06T 3/4053 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
• G06T 7/00 - Image analysis
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Systems and methods for similarity learning in digital pathology are provided. In one aspect, an apparatus for generating training image data includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of histopathology images, classify two or more of the histopathology images as similar or dissimilar, and create a dataset of training image data including the classified histopathology images.

IPC Classes  ?

• G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
• G06N 3/0475 - Generative networks
• G06N 3/094 - Adversarial learning
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Determining spatial analysis data in images each depicting a proximate serial tissue section obtained from a tissue sample. The stained tissue sections include markers (object, markers, etc.) that correspond to material in the tissue sample. The images each include data depicting the markers of the stained tissue sections corresponding to the image. The images are registered and “overlayed” to form a representation of the tissue sample such that intra-section and inter-section measurements between markers in the images correspond to measurements of corresponding material in the tissue sample. A process determines intra-section and/or inter-section measurements between locations of data depicting markers in the images, the measurements representing a distance in 3D space between objects in the tissue sample associated with the markers, and the measurements are stored for use in subsequent processing, for example, spatial analysis of the markers.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/30 - Determination of transform parameters for the alignment of images, i.e. image registration
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces

Abstract

A power off delay system and method is configured to delay termination of electrical power to a digital pathology device in a power off condition. If the apparatus includes a UPS, the power off delay system and method delays termination of electrical power when a power switch is turned off and when a catastrophic power failure occurs. During the delay of the termination of electrical power, the digital pathology device is configured to control the scanning stage system and the glass slide conveyor system and the slide rack conveyor system to place each of these systems into a known state and position all glass slides into a known position prior to the termination of electrical power to the digital pathology device. This allows the digital pathology device to resume normal operation upon power up.

IPC Classes  ?

• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/04 - Details of the conveyor system
• G02B 21/26 - StagesAdjusting means therefor
• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides
• H02J 9/06 - Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over

Abstract

A slide rack gripper apparatus is provided that simultaneously conveys a plurality of glass slides in the protection of a slide rack within a digital slide scanning apparatus. The slide rack gripper apparatus conveys the plurality of glass slides from a slide rack carousel to a scanning stage for processing. The slide rack gripper includes a first motor attached to a base configured to drive a finger mount attached to the base along a first linear axis. The slide rack gripper apparatus also includes a second motor attached to the finger mount and configured to drive opposing gripper fingers attached to the finger mount along a second linear axis. The second motor is also configured to drive individual gripper fingers along a third linear axis to move the gripper fingers toward each other and away from each other to grasp or release a slide rack.

IPC Classes  ?

• B65G 47/90 - Devices for picking-up and depositing articles or materials
• B25J 9/00 - Programme-controlled manipulators
• B25J 15/00 - Gripping heads
• G01N 21/64 - FluorescencePhosphorescence
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/04 - Details of the conveyor system

Goods & Services

Computer hardware, namely, central processing units, servers, scanners, monitors and multiple-screen display monitors, and computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical environments; digital slide information management software for digitizing entire glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents, cross-linked and concurrently viewable for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; computer imaging software for digitizing, analysis and processing of microscope slides and associated data; downloadable computer software for digitizing, analysis, and processing microscope slides and associated data; downloadable scientific and medical multimedia data, namely, high resolution digital images of microscope slides of associated data via the internet. Technical consultation, scientific research services and custom design of computer hardware and software systems in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; virtual microscopy services, namely, converting glass microscope slides to high resolution digital images of slides that can be viewed, integrated with other associated data, managed and analyzed; providing temporary use of non-downloadable computer software for use in database management of digitized images of microscope slides and other associated medical information over computer networks, in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology.

Goods & Services

Automated image analysis computer hardware system comprising printed circuit boards, hard drives, keyboard, monitors, digital scanner, video camera and camera stand; computer software for cellular image and chromosome analysis in the field of molecular biology and genetic research.

Abstract

Methods and systems method for determining quality of an image after a system configuration change. A method includes receiving an indication of a configuration update of an imaging system, processing a test image using the image display system to generate updated test image pixel data for display on the imaging system, determining if the updated test image pixel data is different than the ground truth pixel data of the test image by more than a quality threshold, and in response to the updated test image pixel data being different than the ground truth pixel data of the test image by more than the quality threshold, generate in indicator that the configuration change adversely affected the image generation properties of the imaging system.

IPC Classes  ?

• G09G 5/10 - Intensity circuits

Abstract

c), each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an up-sampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/26 - StagesAdjusting means therefor
• H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
• H04N 25/701 - Line sensors

Abstract

Real-time autofocus. In an embodiment, a scanning apparatus includes an imaging sensor, a focusing sensor, an objective lens, and processor(s) configured to analyze image data captured by the imaging and focusing sensors, and move the objective lens. Real-time autofocus during scanning of a sample is achieved by determining a true-Z value for the objective lens for a point on a sample and for each of a plurality of regions on the sample. The true-Z values and/or surfaces calculated therefrom are used to determine a predicted-Z value for an unscanned region of the sample. The objective lens is adjusted to the predicted-Z value at the beginning of the unscanned region. After scanning the region, a true-Z value is determined for the region and compared to the predicted-Z value. A rescan of the region is initiated if the comparison exceeds a predetermined threshold.

IPC Classes  ?

• G02B 21/24 - Base structure
• G02B 21/00 - Microscopes
• G06T 7/50 - Depth or shape recovery
• H04N 25/711 - Time delay and integration [TDI] registersTDI shift registers

Abstract

A power off delay system and method is configured to delay termination of electrical power to a digital pathology device in a power off condition. If the apparatus includes a UPS, the power off delay system and method delays termination of electrical power when a power switch is turned off and when a catastrophic power failure occurs. During the delay of the termination of electrical power, the digital pathology device is configured to control the scanning stage system and the glass slide conveyor system and the slide rack conveyor system to place each of these systems into a known state and position all glass slides into a known position prior to the termination of electrical power to the digital pathology device. This allows the digital pathology device to resume normal operation upon power up.

IPC Classes  ?

• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/04 - Details of the conveyor system
• G02B 21/26 - StagesAdjusting means therefor
• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides
• H02J 9/06 - Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over

Abstract

A stall detection system is provided that determines if a glass slide in motion during an automated process is at risk for being damaged and stops motion in the event of an unacceptable risk of damage. The system includes one or more motors configured to move a glass slide (directly or indirectly). The motors are configured to generate a load resistance value. The system includes one or more processors that monitor the load resistance value of a motor during motion and compares the load resistance value to a predetermined threshold resistance value to determine the risk of a glass slide being damaged. The predetermined threshold resistance value may correspond to a risk of slide breakage in response to a force applied to any surface of the slide, or a risk of losing a controlling grip on a slide rack, or a risk of a motor skipping a motor step.

IPC Classes  ?

• G01N 35/04 - Details of the conveyor system
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor

Abstract

Image viewing in digital pathology using eye-tracking. In an embodiment, a position of a user's gaze on a graphical user interface, comprising at least a portion of a digital slide image within a macro view, is repeatedly detected based on an output from an eye-tracking device. After detecting a change of the user's gaze from a first position to a second position on the graphical user interface, a view of the digital slide image within the macro view is automatically panned based on the second position, so as to move a position on the digital slide image that corresponds to the second position on the graphical user interface toward a center of the macro view.

IPC Classes  ?

• G06V 40/18 - Eye characteristics, e.g. of the iris
• G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G06F 3/0485 - Scrolling or panning
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A digital pathology apparatus includes a housing with a rail system that allows the housing to slide off of the apparatus to expose the internal elements of the apparatus for easy maintenance. The housing includes a latch and sensor system that securely latches the housing in the closed position and senses when the housing is opened so that the moving parts of the apparatus can be safely stopped to avoid potential injury. The housing also includes electromagnetic shielding on a minimal portion of its interior surface to reduce electromagnetic radiation emanating from the apparatus. The digital pathology apparatus also includes a speakerless audio system that engages with a portion of the interior surface of the housing that is not covered with electromagnetic shielding. The speakerless audio system provides an audio user interface while maintaining a contiguous surface on the housing to cover the digital pathology apparatus.

IPC Classes  ?

• G02B 21/26 - StagesAdjusting means therefor
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

Control processes for a slide-scanning system comprising a carousel with a plurality of rack slots configured to receive slide racks via an exposed portion of the scanning system. In an embodiment, initializing the scanning system comprises automatically homing back-end and front-end components, wherein the front-end components comprise the carousel. An inventory of all slide racks in the carousel is automatically generated. If any slide rack was being processed by any back-end components, the slide rack is automatically unloaded into a corresponding rack slot. In addition, the carousel is automatically positioned to expose a starting subset of the rack slots within the exposed portion. This starting subset may comprise a maximum segment of adjacent empty rack slots.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/08 - Condensers
• G01V 8/20 - Detecting, e.g. by using light barriers using multiple transmitters or receivers
• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides
• G01N 35/02 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor using a plurality of sample containers moved by a conveyor system past one or more treatment or analysis stations
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor

Abstract

Features are disclosed for training a machine learning model to identify objects in histological images. A system may obtain an image and determine a number of objects in the image. For example, the system may determine a percentage of objects in the image with a particular object type. Further, the system may determine a weight. The weight may specify a percentage of the image occupied by objects with the particular object type. The system can generate training set data that includes the image, data identifying the number of objects in the image, and the weight. The system can use the training set data to train a machine learning model to predict a number of objects in a different image and a weight. The system can implement the machine learning model based on training the machine learning model.

IPC Classes  ?

• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Graphical user interface for managing a workflow of a slide scanning system. In an embodiment, the graphical user interface comprises a graphical representation of a carousel used by the scanning system. The graphical representation of the carousel comprises a graphical representation of each of a plurality of rack slots, configured to receive slide racks. The graphical representation of the carousel indicates a position of the carousel, and the graphical representation of each of the plurality of rack slots indicates a status of the represented rack slot and/or a slide rack within the represented rack slot.

IPC Classes  ?

• G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
• G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/02 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor using a plurality of sample containers moved by a conveyor system past one or more treatment or analysis stations
• G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures

Abstract

A segmentation of cell image data obtains cell segmentation data for the nuclei, cytoplasm and cell membranes, which are displayed on an image pane. A data pane is also displayed which contains a table with rows specific to cells and columns specific to cell attributes. In an editing session, a user can select cells for deletion either from the data pane or the image pane. Responsive to a selection via the data pane, the image pane is updated and responsive to a selection via the image pane, the data pane is updated. At any time, the user can command a re-segmentation taking account of the edits, which starts from a version of the previous nuclear segmentation data which has been edited to remove data relating to cells selected for deletion and then from that determines the cytoplasm and cell membrane segmentation data.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/11 - Region-based segmentation

Abstract

Features are disclosed for rendering an image using a GPU and CPU based rendering pipeline. An imaging system may include a GPU and a CPU that each include a portion of an image renderer. A component of the GPU can process the set of image tiles to generate a texture with a wrapped tile coordinate. A component of the GPU can further store the image data as a level of a texture pyramid. As subsequent image data is received, a component of the GPU can access the texture pyramid to determine previously stored image tiles. A component of the GPU can use the previously stored image tiles in rendering the subsequent image data.

IPC Classes  ?

• G06T 11/00 - 2D [Two Dimensional] image generation
• G09G 5/00 - Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
• G06T 1/20 - Processor architecturesProcessor configuration, e.g. pipelining

Goods & Services

Automated image analysis computer hardware system comprising printed circuit boards, hard drives, keyboard, monitors, digital scanner, video camera and camera stand; downloadable and recorded computer software for cellular image and chromosome analysis in the field of molecular biology and genetic research

Abstract

Systems and methods for normalizing image data obtained using multispectral imaging are disclosed. In one aspect, an image analysis apparatus includes an imaging device configured to perform a multispectral scan of a tissue sample to generate image data, a processor, and at least one computer-readable memory. The processor is configured to receive the image data from the imaging device and preprocess the image data to generate a normalization factor based on pixel values of the image data within at least one sub-region of the image data. The processor is also configured to provide the preprocessed image data and the normalization factor as inputs to a machine learning algorithm and determine, based on an output of the machine learning algorithm, whether the image data is indicative of a disease present in the tissue sample.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06N 3/02 - Neural networks
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Features are disclosed for imaging block and slice samples using an imaging system. The imaging system can link the images by identifiers associated with the block and slice samples. The imaging system can train a machine learning algorithm based on correctly linked images. In some embodiments, the trained machine learning algorithm may include an image analysis module or a convolutional neural network. The imaging system can use the trained machine learning algorithm in order to determine a confidence score of a match between the block and the slice samples. The trained machine learning algorithm can use features of the block and the slice samples such as shape and tissue morphology to determine whether the samples match. In some embodiments, when the confidence score is below a certain threshold, the imaging system can alert a user that the samples may not match.

IPC Classes  ?

• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06T 7/00 - Image analysis
• G01N 1/30 - StainingImpregnating

Abstract

An input device allows a user to manipulate an image displayed by a user interface (UI) of a computer. The input device includes a housing, a first rotatable control knob supported by the housing, and a second rotatable control knob supported by the housing. The first and second rotatable control knobs allow the user to perform at least zooming and panning manipulations of the image on the UI. The input device can further include a third rotatable control knob and a touch pad. The input device can be configured as a keyboard.

IPC Classes  ?

• G06F 3/02 - Input arrangements using manually operated switches, e.g. using keyboards or dials
• G06F 3/0362 - Pointing devices displaced or positioned by the userAccessories therefor with detection of 1D translations or rotations of an operating part of the device, e.g. scroll wheels, sliders, knobs, rollers or belts
• G06F 3/0485 - Scrolling or panning

Abstract

A slide rack inventory and reinsertion system for use with a digital slide scanning apparatus is provided that determines, prior to scanning of glass slides in a slide rack, a status of each slot in the slide rack as properly occupied, improperly occupied, or empty. The system also determines whether a slide that has been removed from the slide rack for processing has been properly reinserted into the slide rack.

IPC Classes  ?

• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 21/84 - Systems specially adapted for particular applications
• G01V 8/12 - Detecting, e.g. by using light barriers using one transmitter and one receiver

Abstract

Systems and methods for capturing a digital image of a slide using an imaging line sensor and a focusing line sensor. In an embodiment, a beam-splitter is optically coupled to an objective lens and configured to receive one or more images of a portion of a sample through the objective lens. The beam-splitter simultaneously provides a first portion of the one or more images to the focusing sensor and a second portion of the one or more images to the imaging sensor. A processor controls the stage and/or objective lens such that each portion of the one or more images is received by the focusing sensor prior to it being received by the imaging sensor. In this manner, a focus of the objective lens can be controlled using data received from the focusing sensor prior to capturing an image of a portion of the sample using the imaging sensor.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

Physical calibration slide comprising a plurality of etched features. The etched features may comprise two or more of a slanted Ronchi ruling feature comprising at least one set of parallel lines that are slanted with respect to a long and short axis of the slide, a straight Ronchi ruling feature comprising at least one set of parallel lines that are parallel to either the long or short axis, a star target feature comprising a circle with a plurality of wedge pairs, a crosshair feature comprising at least one crosshair, a clear area, a letter-O feature comprising a circle, a resolution target feature comprising one or more resolution targets, a bullseye feature comprising a two-dimensional array of bullseyes, a triangle feature comprising at least one isosceles triangle, or a symmetric corers feature comprising two symmetric sets of geometric shapes arranged in an L-shape.

IPC Classes  ?

• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides
• G01N 1/28 - Preparing specimens for investigation
• G01N 1/32 - PolishingEtching

Abstract

Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.

IPC Classes  ?

• G02B 21/00 - Microscopes
• H04N 23/67 - Focus control based on electronic image sensor signals
• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• H04N 3/06 - Scanning details of television systemsCombination thereof with generation of supply voltages by optical-mechanical means only having a moving lens or other refractor
• H04N 23/90 - Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• H04N 23/56 - Cameras or camera modules comprising electronic image sensorsControl thereof provided with illuminating means

Abstract

A digital pathology system comprising an AI processing module configured to invoke an instance of an AI processing application for processing image data from a histological image and an application module configured to invoke an instance of an application operable to perform an image processing task on a histological image associated with a patient record, wherein the image processing task includes an AI element. The application creates processing jobs to handle the AI elements of its task which are handled by the AI processing module. The AI processing module may be a CNN that processes a histological image to identify tumors by classifying image pixels into one of multiple tissue classes of tumorous or non-tumorous tissue. A test ordering module automatically determines based on identified tissue classes whether additional tests should be performed on the tissue sample. For each additional test, an order is automatically created and submitted. Advantageously, upon first review by a pathologist, the patient record includes the histological image and results from the automatically ordered additional tests.

IPC Classes  ?

• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
• G06N 3/08 - Learning methods

Abstract

A computer apparatus and method for identifying and visualizing tumors in a histological image and measuring a tumor margin are provided. A CNN is used to classify pixels in the image according to whether they are determined to relate to non-tumorous tissue, or one or more classes for tumorous tissue. Segmentation is carried out based on the CNN results to generate a mask that marks areas occupied by individual tumors. Summary statistics for each tumor are computed and supplied to a filter which edits the segmentation mask by filtering out tumors deemed to be insignificant. Optionally, the tumors that pass the filter may be ranked according to the summary statistics, for example in order of clinical relevance or by a sensible order of review for a pathologist. A visualization application can then display the histological image having regard to the segmentation mask, summary statistics and/or ranking. Tumor masses extracted by resection are painted with an ink to highlight its surface region. The CNN is trained to distinguish ink and no-ink tissue as well as tumor and no-tumor tissue. The CNN is applied to the histological image to generate an output image whose pixels are assigned to the tissue classes. Tumor margin status of the tissue section is determined by the presence or absence of tumor-and-ink classified pixels. Tumor margin involvement and tumor margin distance are determined by computing additional parameters based on classification-specified inter-pixel distance parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
• G06N 3/08 - Learning methods
• G06F 18/24 - Classification techniques
• G06F 18/214 - Generating training patternsBootstrap methods, e.g. bagging or boosting
• G06F 3/04842 - Selection of displayed objects or displayed text elements

Abstract

A CNN is applied to a histological image to identify areas of interest. The CNN classifies pixels according to relevance classes including one or more classes indicating levels of interest and at least one class indicating lack of interest. The CNN is trained on a training data set including data which has recorded how pathologists have interacted with visualizations of histological images. In the trained CNN, the in-terest-based pixel classification is used to generate a segmentation mask that defines areas of interest. The mask can be used to indicate where in an image clinically relevant features may be located. Further, it can be used to guide variable data compression of the histological image. Moreover, it can be used to control loading of image data in either a client-server model or within a memory cache policy. Furthermore, a histological image of a tissue sample of a tissue type that has been treated with a test compound is image processed in order to detect areas where toxic reactions to the test compound may have occurred. An autoencoder is trained with a training data set comprising histological images of tissue samples which are of the given tissue type, but which have not been treated with the test compound. The trained autoencoder is applied to detect tissue areas by their deviation from the normal variation seen in that tissue type as learnt by the training process, and so build up a toxicity map of the image. The toxicity map can then be used to direct a toxicological pathologist to examine the areas identified by the autoencoder as lying outside the normal range of heterogeneity for the tissue type. This makes the pathologist's review quicker and more reliable. The toxicity map can also be overlayed with the segmentation mask indicating areas of interest. When an area of interest and an area identified as lying outside the normal range of heterogeneity for the tissue type, and increased confidence score is applied to the overlapping area.

IPC Classes  ?

• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
• G06T 7/00 - Image analysis
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

Image viewing in digital pathology using eye-tracking. In an embodiment, a position of a user's gaze on a graphical user interface, comprising at least a portion of a digital slide image within a macro view, is repeatedly detected based on an output from an eye-tracking device. After detecting a change of the user's gaze from a first position to a second position on the graphical user interface, a view of the digital slide image within the macro view is automatically panned based on the second position, so as to move a position on the digital slide image that corresponds to the second position on the graphical user interface toward a center of the macro view.

IPC Classes  ?

• G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G06F 3/0485 - Scrolling or panning
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A fixed reference edge system that guides a glass slide from a slot of a slide rack onto a scanning stage and guides the glass slide from the scanning stage into the slot of the slide rack. In an embodiment, the fixed reference edge has a first side that is parallel to a side of the slot of the slide rack. The system comprises an assembly that includes a push bar configured to push the slide from the slot onto the scanning stage, and a pull bar configured to pull the slide from the scanning stage into the slot of the slide rack. When the slide is pulled into the slide rack, the long edge of the slide is pressed against the first side of the fixed reference edge to maintain a parallel orientation between the slide and the slot of the slide rack.

IPC Classes  ?

• G02B 21/26 - StagesAdjusting means therefor
• G01N 1/02 - Devices for withdrawing samples
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• B65G 49/06 - Conveying systems characterised by their application for specified purposes not otherwise provided for for fragile or damageable materials or articles for fragile sheets, e.g. glass
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor

Abstract

A digital slide scanning apparatus slide rack carousel allows continuous loading and unloading of slide racks into the carousel while the digital slide scanning apparatus is simultaneously digitizing glass slides. The slide rack carousel includes a base having an interior portion of its upper surface at an angle. The slide rack carousel also includes plural rack spacers extending upward from the base and adjacent rack spacers define a rack slot. Each rack spacer also includes a rack stopper on each side such that adjacent rack spacers have rack stoppers facing each other. The rack stoppers prevent a slide rack from moving further toward the center of the carousel than desired.

IPC Classes  ?

• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/02 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor using a plurality of sample containers moved by a conveyor system past one or more treatment or analysis stations
• G01N 35/04 - Details of the conveyor system

Abstract

A digital slide scanning apparatus includes a safety light curtain that operates to disable the motor that rotates the carousel when the presence of an object (e.g., the fingers of an operator) is detected within a predetermined area of the carousel. The light curtain also operates to disable the motor that rotates the carousel when an improperly positioned glass slide or slide rack is detected. The digital slide scanning apparatus also includes a multi-color status indicator for each rack slot that indicates the rack slot location of an improperly positioned glass slide or slide rack.

IPC Classes  ?

• G01N 1/00 - SamplingPreparing specimens for investigation
• G01N 35/02 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor using a plurality of sample containers moved by a conveyor system past one or more treatment or analysis stations
• B01L 3/00 - Containers or dishes for laboratory use, e.g. laboratory glasswareDroppers
• F16P 3/14 - Safety devices acting in conjunction with the control or operation of a machineControl arrangements requiring the simultaneous use of two or more parts of the body with means, e.g. feelers, which in case of the presence of a body part of a person in or near the danger zone influence the control or operation of the machine the means being photocells or other devices sensitive without mechanical contact
• B01L 9/00 - Supporting devicesHolding devices
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/04 - Details of the conveyor system

Abstract

A slide rack clamp apparatus that secures a slide rack in a digital slide scanning apparatus. In an embodiment, the slide rack clamp apparatus includes an upper clamp and a lower clamp. Each clamp comprises one or more clamp projections, which are configured to engage one or more recesses in engagement surfaces of a plurality of different slide racks from different manufacturers. The lower clamp is driven by a motor along a linear axis to engage the lower clamp projections with the one or more slide rack recesses of the bottom surface of the slide rack. The motor drives the lower clamp and the engaged slide rack upward to engage the one or more slide rack recesses of the top surface of the slide rack with the clamp projections of the upper clamp to fully engage the slide rack between the upper clamp and the lower clamp.

IPC Classes  ?

• G01N 35/10 - Devices for transferring samples to, in, or from, the analysis apparatus, e.g. suction devices, injection devices
• G01N 21/64 - FluorescencePhosphorescence
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor

Abstract

Subpixel line scanning. A slide scanning device comprises a plurality of line sensors (112a, 112b, 112c), each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an up-sampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.

IPC Classes  ?

• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• G02B 27/58 - Optics for apodization or superresolutionOptical synthetic aperture systems

Abstract

Real-time autofocus. In an embodiment, a scanning apparatus includes an imaging sensor, a focusing sensor, an objective lens, and processor(s) configured to analyze image data captured by the imaging and focusing sensors, and move the objective lens. Real-time autofocus during scanning of a sample is achieved by determining a true-Z value for the objective lens for a point on a sample and for each of a plurality of regions on the sample. The true-Z values and/or surfaces calculated therefrom are used to determine a predicted-Z value for an unscanned region of the sample. The objective lens is adjusted to the predicted-Z value at the beginning of the unscanned region. After scanning the region, a true-Z value is determined for the region and compared to the predicted-Z value. A rescan of the region is initiated if the comparison exceeds a predetermined threshold.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/24 - Base structure
• G06T 7/50 - Depth or shape recovery
• H04N 5/372 - Charge-coupled device [CCD] sensors; Time delay and integration [TDI] registers or shift registers specially adapted for SSIS

Abstract

Systems and methods for capturing a digital image of a slide using an imaging line sensor and a focusing line sensor. In an embodiment, a beam-splitter is optically coupled to an objective lens and configured to receive one or more images of a portion of a sample through the objective lens. The beam-splitter simultaneously provides a first portion of the one or more images to the focusing sensor and a second portion of the one or more images to the imaging sensor. A processor controls the stage and/or objective lens such that each portion of the one or more images is received by the focusing sensor prior to it being received by the imaging sensor. In this manner, a focus of the objective lens can be controlled using data received from the focusing sensor prior to capturing an image of a portion of the sample using the imaging sensor.

IPC Classes  ?

• G02B 21/00 - Microscopes
• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

A segmentation of cell image data obtains cell segmentation data for the nuclei, cytoplasm and cell membranes, which are displayed on an image pane. A data pane is also displayed which contains a table with rows specific to cells and columns specific to cell attributes. In an editing session, a user can select cells for deletion either from the data pane or the image pane. Responsive to a selection via the data pane, the image pane is updated and responsive to a selection via the image pane, the data pane is updated. At any time, the user can command a re-segmentation taking account of the edits, which starts from a version of the previous nuclear segmentation data which has been edited to remove data relating to cells selected for deletion and then from that determines the cytoplasm and cell membrane segmentation data.

IPC Classes  ?

• G06T 7/11 - Region-based segmentation
• G06T 7/00 - Image analysis

Abstract

A slide rack inventory and reinsertion system for use with a digital slide scanning apparatus is provided that determines, prior to scanning of glass slides in a slide rack, a status of each slot in the slide rack as properly occupied, improperly occupied, or empty. The system also determines whether a slide that has been removed from the slide rack for processing has been properly reinserted into the slide rack.

IPC Classes  ?

• G01V 8/12 - Detecting, e.g. by using light barriers using one transmitter and one receiver
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 21/84 - Systems specially adapted for particular applications

Abstract

A digital scanning apparatus is provided that includes imaging and focusing sensors and a processor to analyze the image data captured by the imaging and focusing sensors and adjust the focus of the scanning apparatus in real time during a scanning operation. The individual pixels of the imaging sensor are all in the same image plane with respect to the optical path of the digital scanning apparatus. The individual pixels of the focusing sensor are each in a different image plane with respect to the optical path, and one pixel of the focusing sensor is on the same image plane as the image sensor. The processor analyzes image data from the imaging sensor and the focusing sensor and determines a distance and direction to adjust the relative position of an objective lens and a stage of the digital scanning apparatus to achieve optimal focus during the scanning operation.

IPC Classes  ?

• G02B 7/38 - Systems for automatic generation of focusing signals using image sharpness techniques measured at different points on the optical axis
• G02B 21/02 - Objectives
• G02B 21/26 - StagesAdjusting means therefor
• G02B 7/09 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification adapted for automatic focusing or varying magnification
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• H04N 5/232 - Devices for controlling television cameras, e.g. remote control

Abstract

A digital pathology imaging apparatus includes a single line scan camera sensor optically coupled with first and second optical paths. In a first embodiment, transmission mode illumination and oblique mode illumination are simultaneously used during a single stage movement that captures a low resolution macro image of the entire sample area and the entire label area of the slide via the first optical path. In a second embodiment, transmission mode illumination is used during a first stage movement that captures a low resolution macro image of at least the entire sample area via the first optical path and oblique mode illumination is used during a second stage movement that captures a low resolution macro image of at least the entire label area via the first optical path.

IPC Classes  ?

• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• G02B 21/00 - Microscopes
• G02B 21/26 - StagesAdjusting means therefor
• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides
• G02B 21/24 - Base structure

Abstract

Color calibration for digital pathology is provided. A standard glass slide is prepared with a specimen having zero or more stains. The specimen is scanned a first time using a hyperspectral imaging system to produce a first digital image having XYZ color values. The specimen is scanned a second time using a digital pathology imaging system to produce a second digital image having RGB color values. The first and second digital images are then registered against each other to align the digital image data. Individual pixels of the first and second images may be combined in the registration process so that the first and second digital images have substantially similar pixel sizes. A lookup table is generated to associate XYZ color values to RGB color values. Once the lookup table has been generated, it can be used to present RGB color on a display using the corresponding XYZ color.

IPC Classes  ?

• G06T 7/80 - Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
• G06T 7/90 - Determination of colour characteristics
• G06T 7/00 - Image analysis
• G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
• G01J 3/46 - Measurement of colourColour measuring devices, e.g. colorimeters
• G01J 3/50 - Measurement of colourColour measuring devices, e.g. colorimeters using electric radiation detectors
• G01N 1/30 - StainingImpregnating
• G01J 1/08 - Arrangements of light sources specially adapted for photometry
• G01J 3/10 - Arrangements of light sources specially adapted for spectrometry or colorimetry
• G01J 3/28 - Investigating the spectrum
• G02B 21/32 - Micromanipulators structurally combined with microscopes
• G01N 21/27 - ColourSpectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• G06T 3/00 - Geometric image transformations in the plane of the image
• G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting

Abstract

Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.

IPC Classes  ?

• G02B 7/28 - Systems for automatic generation of focusing signals
• G02B 21/00 - Microscopes
• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes
• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• H04N 5/369 - SSIS architecture; Circuitry associated therewith
• G02B 7/38 - Systems for automatic generation of focusing signals using image sharpness techniques measured at different points on the optical axis
• G03B 13/36 - Autofocus systems
• H04N 5/232 - Devices for controlling television cameras, e.g. remote control

Abstract

Physical calibration slide comprising a plurality of etched features. The etched features may comprise two or more of a slanted Ronchi ruling feature comprising at least one set of parallel lines that are slanted with respect to a long and short axis of the slide, a straight Ronchi ruling feature comprising at least one set of parallel lines that are parallel to either the long or short axis, a star target feature comprising a circle with a plurality of wedge pairs, a crosshair feature comprising at least one crosshair, a clear area, a letter-O feature comprising a circle, a resolution target feature comprising one or more resolution targets, a bullseye feature comprising a two-dimensional array of bullseyes, a triangle feature comprising at least one isosceles triangle, or a symmetric corners feature comprising two symmetric sets of geometric shapes arranged in an L-shape.

IPC Classes  ?

• G02B 21/34 - Microscope slides, e.g. mounting specimens on microscope slides

Abstract

Control processes for a slide-scanning system comprising a carousel with a plurality of rack slots configured to receive slide racks via an exposed portion of the scanning system. In an embodiment, initializing the scanning system comprises automatically homing back-end and front-end components, wherein the front-end components comprise the carousel. An inventory of all slide racks in the carousel is automatically generated. If any slide rack was being processed by any back-end components, the slide rack is automatically unloaded into a corresponding rack slot. In addition, the carousel is automatically positioned to expose a starting subset of the rack slots within the exposed portion. This starting subset may comprise a maximum segment of adjacent empty rack slots.

IPC Classes  ?

• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G01N 35/02 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor using a plurality of sample containers moved by a conveyor system past one or more treatment or analysis stations

Abstract

A digital pathology apparatus includes a housing with a rail system that allows the housing to slide off of the apparatus to expose the internal elements of the apparatus for easy maintenance. The housing includes a latch and sensor system that securely latches the housing in the closed position and senses when the housing is opened so that the moving parts of the apparatus can be safely stopped to avoid potential injury. The housing also includes electromagnetic shielding on a minimal portion of its interior surface to reduce electromagnetic radiation emanating from the apparatus. The digital pathology apparatus also includes a spearkerless audio system that engages with a portion of the interior surface of the housing that is not covered with electromagnetic shielding. The speakerless audio system provides an audio user interface while maintaining a contiguous surface on the housing to cover the digital pathology apparatus.

IPC Classes  ?

• G02B 21/24 - Base structure
• G02B 21/36 - Microscopes arranged for photographic purposes or projection purposes

Abstract

Graphical user interface for managing a workflow of a slide scanning system. In an embodiment, the graphical user interface comprises a graphical representation of a carousel used by the scanning system. The graphical representation of the carousel comprises a graphical representation of each of a plurality of rack slots, configured to receive slide racks. The graphical representation of the carousel indicates a position of the carousel, and the graphical representation of each of the plurality of rack slots indicates a status of the represented rack slot and/or a slide rack within the represented rack slot.

IPC Classes  ?

• G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor

Abstract

A stall detection system is provided that determines if a glass slide in motion during an automated process is at risk for being damaged and stops motion in the event of an unacceptable risk of damage. The system includes one or more motors configured to move a glass slide (directly or indirectly). The motors are configured to generate a load resistance value. The system includes one or more processors that monitor the load resistance value of a motor during motion and compares the load resistance value to a predetermined threshold resistance value to determine the risk of a glass slide being damaged. The predetermined threshold resistance value may correspond to a risk of slide breakage in response to a force applied to any surface of the slide, or a risk of losing a controlling grip on a slide rack, or a risk of a motor skipping a motor step.

IPC Classes  ?

• G05B 19/4062 - Monitoring servoloop, e.g. overload of servomotor, loss of feedback or reference

Abstract

Medical image based collaboration system and methods are provided. A collaboration server 40 creates a medical image based case in response to a request from a requesting system 10 and populates the case with the minimum required information comprising at least a digital medical image and a case number. The collaboration server 40 provides the medical image based case to a consulting system 30 and receives analysis information in response. The collaboration server 40 stores the analysis information in association with the medical image based case and provides the analysis information to the consulting system 30 to complete the medical image based collaboration.

IPC Classes  ?

• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G06Q 10/101 - Collaborative creation, e.g. joint development of products or services
• G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• G06Q 10/10 - Office automationTime management
• G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
• G06Q 50/22 - Social work or social welfare, e.g. community support activities or counselling services

Abstract

A stuck slide determination system is provided that determines if a slide (e.g., glass slide), positioned on a scanning stage at the start of the scanning process, gets stuck and does not move along with the scanning stage after the scanning process commences. In an embodiment, the system includes a sensor having a transmitter and receiver that are relatively positioned to detect the presence of the stage or a slide or the absence of the stage or a slide. When the scanning stage begins to move at the start of the scanning process, a processor monitors a signal from the sensor and determines if the slide is improperly positioned after the scanning process has commenced. If the slide is improperly positioned, the processor stops movement of the scanning stage in order to protect the slide from damage.

IPC Classes  ?

• B65G 43/00 - Control devices, e.g. for safety, warning or fault-correcting
• G01V 8/12 - Detecting, e.g. by using light barriers using one transmitter and one receiver
• G01N 35/00 - Automatic analysis not limited to methods or materials provided for in any single one of groups Handling materials therefor
• G02B 21/00 - Microscopes
• G01N 21/64 - FluorescencePhosphorescence

Abstract

A CNN is applied to a histological image to identify areas of interest. The CNN classifies pixels according to relevance classes including one or more classes indicating levels of interest and at least one class indicating lack of interest. The CNN is trained on a training data set including data which has recorded how pathologists have interacted with visualizations of histological images. In the trained CNN, the interest-based pixel classification is used to generate a segmentation mask that defines areas of interest. The mask can be used to indicate where in an image clinically relevant features may be located. Further, it can be used to guide variable data compression of the histological image. Moreover, it can be used to control loading of image data in either a client-server model or within a memory cache policy. Furthermore, a histological image of a tissue sample of a tissue type that has been treated with a test compound is image processed in order to detect areas where toxic reactions to the test compound may have occurred. An autoencoder is trained with a training data set comprising histological images of tissue samples which are of the given tissue type, but which have not been treated with the test compound. The trained autoencoder is applied to detect tissue areas by their deviation from the normal variation seen in that tissue type as learnt by the training process, and so build up a toxicity map of the image. The toxicity map can then be used to direct a toxicological pathologist to examine the areas identified by the autoencoder as lying outside the normal range of heterogeneity for the tissue type. This makes the pathologist's review quicker and more reliable. The toxicity map can also be overlayed with the segmentation mask indicating areas of interest. When an area of interest and an area identified as lying outside the normal range of heterogeneity for the tissue type, and increased confidence score is applied to the overlapping area.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• G06K 9/46 - Extraction of features or characteristics of the image
• G06K 9/62 - Methods or arrangements for recognition using electronic means

Abstract

A digital pathology system comprising an AI processing module configured to invoke an instance of an AI processing application for processing image data from a histological image and an application module configured to invoke an instance of an application operable to perform an image processing task on a histological image associated with a patient record, wherein the image processing task includes an AI element. The application creates processing jobs to handle the AI elements of its task which are handled by the AI processing module. The AI processing module may be a CNN that processes a histological image to identify tumors by classifying image pixels into one of multiple tissue classes of tumorous or non-tumorous tissue. A test ordering module automatically determines based on identified tissue classes whether additional tests should be performed on the tissue sample. For each additional test, an order is automatically created and submitted. Advantageously, upon first review by a pathologist, the patient record includes the histological image and results from the automatically ordered additional tests.

IPC Classes  ?

• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems