Abstract: Disclosed is a system for analysis of microscopic image data which includes a data processing system. Pixel classification data for each of a plurality of pixels of the microscopic image data are read. The pixel classification data include for each of the pixels of the microscopic image data, binary or probabilistic classification data for classifying the pixel of the microscopic image data into one or more object classes of pre-defined objects which are shown by the image. At least a portion of the pixels of the microscopic image data are grouped to form one or more pixels groups. For each of the pixel groups, probabilistic group classificati on data are calculated depending on the pixel classification data of the pixels of the respective group. The probabilistic group classification data are indicative of a probability that the group shows at least a portion of an object of the respective object class.

Abstract: A process for converting an arbitrary input digital pathology image into an output digital pathology image that shares statistical information with a reference image. The input digital pathology image is separated into two or more image sections. Each image section is encoded, using a first convolutional neural network, into one or more feature maps. The one or more feature maps of each image section are modified based on statistical information derived from a reference image. The modified feature map(s) of each image section is/are then decoded to construct a respective image section for an output image. The constructed image sections for an output image then form the output image.

Abstract: The invention relates to a method for use in characterizing lesions in radiology images, comprising performing a computer-based analysis of a pathology image of a sample of a lesion of a subject in order to recognize tissue and/or cellular characteristics of the lesion, wherein the analysis produces a derived pathology image that represents the recognized tissue and/or cellular characteristics, computing one or more radiology features for the lesion from a radiology image of the lesion, and determining correlations between the computed one or more radiology features and the recognized tissue and/or cellular characteristics. With this method, biological ground truth information can be used to identify radiology features that are indicative of certain tissue and/or cellular characteristics of lesions and that may therefore be better suited for characterizing the lesions.

Abstract: The present invention relates to an examining device (1) for processing and analyzing an image of a bio sample, an examining method for processing and analyzing an image of a bio sample, a computer program element for controlling such device (1), and a corresponding computer readable medium. The examining device (1) for processing and analyzing an image of a bio sample comprises an interface unit, an image analyzing unit, and a display unit. The interface unit is configured to provide an image of a bio sample. The image analyzing unit is configured to indicate a region of interest in the image as reference region, to extract a characteristic of the reference region from the image and to analyze the image for alternative regions with a similar characteristic. The display unit is configured to display the result of the analysis for alternative regions with a similar characteristic.

Abstract: Disclosed is a system for analysis of microscopic image data representing a plurality of images acquired from cells. The system comprises a data processing system which is configured to read and/or generate (120) segmentation data for each of the images. For each of the images, the segmentation data are indicative of a segmentation of at least a portion of the respective image into one or more image regions so that each of the image regions is a member of one or more predefined classes of image content. The data processing system further generates co-registration data using at least portions of the segmentation data for co-registering at least portions of different ones of the images. The data processing system further generates mapping data using at least portions of the segmentation data for mapping between image regions of different images.

Abstract: The ability to obtain and digitise pathology samples (such as in histopathology or cytopathology) has opened up the possibility of accurate and automated computer operated analysis, or computer-assisted analysis, when diagnosing a wide range of medical conditions. A typical digital pathology image analysis pipeline involves a large number of image pre-processing and processing operations. Small changes in the parameters used in these algorithms might lead to significant changes in the eventual pathological finding. Accordingly, the present application proposes to perform a sensitivity analysis on a digital pathology image analysis pipeline to assess the sensitivity of a given pathology result to changes of parameters in the digital pathology image analysis pipeline.

Abstract: Disclosed is a system for analysis of microscopic image data acquired from biological cells. The system includes a data processing system which is configured to read the image data and determine a plurality of vertices, wherein each of the vertices represents a location of an entity of interest within a region of interest of the image data. The data processing system generates a plurality of graphs, wherein for each of the graphs, the generation of the respective graph includes generating a plurality of edges, wherein each of the edges has two of the plurality of vertices associated therewith. For each of the graphs one or more vertex sets are identified, each of which consisting of one or more of the plurality of vertices. The data processing system further determines, for each of the graphs, a number of the identified vertex sets.

Abstract: Disclosed is a system for analysis of microscopic image data which includes a data processing system. Pixel classification data for each of a plurality of pixels of the microscopic image data are read. The pixel classification data include for each of the pixels of the microscopic image data, binary or probabilistic classification data for classifying the pixel of the microscopic image data into one or more object classes of pre-defined objects which are shown by the image. At least a portion of the pixels of the microscopic image data are grouped to form one or more pixels groups. For each of the pixel groups, probabilistic group classificati on data are calculated depending on the pixel classification data of the pixels of the respective group. The probabilistic group classification data are indicative of a probability that the group shows at least a portion of an object of the respective object class.

Abstract: The present invention relates to detecting objects in medical images. In order to provide an improved detection of objects in medical images, a medical image detection device (10) is provided that comprises an image data input (12) and a processing unit (14). The image data input is configured to receive image data of a biological sample. The processing unit comprises a detector (16) and a classifier (18). The detector is configured to detect objects of interest in the sample by a detection in the image data of at least one predetermined object feature. The detected objects being candidate objects, wherein the candidate objects comprise true positives and possible false positives. Further, the classifier is configured to classify the possible false positives as false positives or as true positives. The classifier is a trained classifier, trained specifically to recognize the false positives of the detector.

Abstract: A method for registration of images of tissue slices comprises: receiving a first image of a first tissue slice and a second image of a second tissue slice, both tissue slices being prepared from the same tissue block; determining an unreliable area in the first image showing folded tissue; and registering the first image and the second image by registering an area of the first image and the second image outside of the unreliable area.

Abstract: The present invention relates to a system for generating a synthetic 2D image with an enhanced depth of field of a biological sample. It is described to acquire (110) with a microscope-scanner (20) first image data at a first lateral position of the biological sample and second image data at a second lateral position of the biological sample. The microscope-scanner is used to acquire (120) third image data at the first lateral position and fourth image data at the second lateral position, wherein the third image data is acquired at a depth that is different than that for the first image data and the fourth image data is acquired at a depth that is different than that for the second image data. First working image data is generated (130) for the first lateral position, the generation comprising processing the first image data and the third image data by a focus stacking algorithm.

Abstract: The present disclosure pertains to a method and system configured for generating one or more statements. In some embodiments, the system comprises at least one processor; memory operatively connected with the at least one processor; a communication component operatively connected to the at least one processor and configured to communicate with a user device via a network. The at least one processor is configure by machine-readable instructions to receive one or more measurements pertaining to a parameter of a user from the user device; generate one or more statements based on the one or more measurements and one or more templates; and transmit, via the network, the one or more statements for presentation on the user device.

Abstract: The present invention relates to a system for generating a synthetic 2D image with an enhanced depth of field of a biological sample. It is described to acquire (110) with a microscope-scanner (20) first image data at a first lateral position of the biological sample and second image data at a second lateral position of the biological sample. The microscope-scanner is used to acquire (120) third image data at the first lateral position and fourth image data at the second lateral position, wherein the third image data is acquired at a depth that is different than that for the first image data and the fourth image data is acquired at a depth that is different than that for the second image data. First working image data is generated (130) for the first lateral position, the generation comprising processing the first image data and the third image data by a focus stacking algorithm.

Abstract: The present invention relates to an apparatus for generating a synthetic 2D image with an enhanced depth of field of an object. It is described to acquire (110) with an image acquisition unit (20) first image data at a first lateral position of the object and second image data at a second lateral position of the object. The image acquisition unit is used to acquire (120) third image data at the first lateral position and fourth image data at the second lateral position, wherein the third image data is acquired at a down range distance that is different than that for the first image data and the fourth image data is acquired at a down range distance that is different than that for the second image data. First working image data is generated (130) for the first lateral position, the generation comprising processing the first image data and the third image data by a focus stacking algorithm.

Abstract: A method for registration of images of tissue slices comprises: receiving a first image of a first tissue slice and a second image of a second tissue slice, both tissue slices being prepared from the same tissue block; determining an unreliable area in the first image showing folded tissue; and registering the first image and the second image by registering an area of the first image and the second image outside of the unreliable area.

Abstract: A method for registration of images of tissue slices comprises: receiving a first image (18a) of a first tissue slice (14a) and a second image (18b) of a second tissue slice (14b), both tissue slices being prepared from the same tissue block (10); determining an unreliable area (27) in the first image (14a) showing folded tissue (15); and registering the first image (14a) and the second image by registering an area of the first image and the second image outside of the unreliable area.

Abstract: An apparatus (MDS) and related method for image processing. The apparatus includes a multi-modal matcher (M). The matcher (M) operates to match a first reference (RF1) image against a stream (LF) of image frames (F1, F2). Once a match is found, the current reference image (RF1) is exchanged for a matching frame from the stream. The matcher (M) then attempts matching against subsequent frames in the stream by now using said matched frame as a new reference image. Once a further frame (Fm) is found that matches said new reference image, said further frame (Fm) is output as a best match.

Abstract: The present invention relates to a method for registering and visualizing at least two images, the method comprising the steps of: measuring (S1) a navigation speed used by a user during a scrollable and/or zoomable visualization of a first image of the at least two images and comparing the navigation speed with a navigation speed threshold value; visualizing (S2) the first image by solving deformations of the first image using a first level of computational load, if the navigation speed is below the navigation speed threshold value; and visualizing (S3) the first image by solving deformations of the first image using a second level of computational load, if the navigation speed is above the navigation speed threshold value.

Abstract: The present invention relates to a device for obtaining a vital sign of a subject, comprising an interface (20) for receiving a set of image frames of a subject, a motion analysis unit (30) for analyzing at least one measurement area within the image frames of the set of image frames and for characterizing motion of the subject within the set of image frames, a signal extraction unit (40) for extracting photoplethysmographic, PPG, signals from the set of image frames using the characterization of motion of the subject within the set of image frames, and a vital signs determination unit (50) for determining vital sign information from the extracted PPG signals. The motion analysis unit comprises a motion estimation unit (32), a spatial characteristic extraction unit (34), and a motion characterization unit (36).

Abstract: A system for processing an image comprises a region detector (1). The region detector comprises an artifact detector (7) for detecting a region comprising an artifact in the image. The system comprises a parameter determining unit (2) for determining a parameter, based on a portion of the image excluding the detected region. The system comprises an image processing module (3) for processing the image, using the derived parameter. The system comprises a display unit (5) for displaying the processed image with an indication of the detected region. The parameter determined by the parameter determining unit (2) can comprise a normalization parameter, and the image processing module (3) can be arranged for performing a normalization of the image according to the normalization parameter.