Abstract: The present disclosure is directed to a computer system designed to (i) receive a series of images as input; (ii) compute a number of metrics derived from focus features and color separation features within the images; and (iii) evaluate the metrics to return (a) an identification of the most suitable z-layer in a z-stack, given a series of z-layer images in a z-stack; and/or (b) an identification of those image tiles that are more suitable for cellular based scoring by a medical professional, given a series of image tiles from an area of interest of a whole slide scan.

Abstract: The present disclosure is directed to a computer system designed to (i) receive a series of images as input; (ii) compute a number of metrics derived from focus features and color separation features within the images; and (iii) evaluate the metrics to return (a) an identification of the most suitable z-layer in a z-stack, given a series of z-layer images in a z-stack; and/or (b) an identification of those image tiles that are more suitable for cellular based scoring by a medical professional, given a series of image tiles from an area of interest of a whole slide scan.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: Techniques are provided for stitching tile images. A local registration can be performed to determine spatial relationships between pairs of adjacent tile images, in which the spatial relationships may be determined using normalized cross correlation (NCC) scores computed within a multi-resolution framework. A global placement can be performed to position all scanned tile images relative to one another. The global placement is determined with weighted least squares utilizing the determined spatial relationships between all adjacent greyscale tile images and the NCC scores as weights.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: This disclosure describes methods, kits, and systems for scoring the immune response to cancer through examination of tissue infiltrating lymphocytes (TILs). Methods of scoring the immune response in cancer using tissue infiltrating lymphocytes include detecting CD3, CD8, CD20, and FoxP3 within the sample and scoring the detection manually or scoring the digital images of the staining with the aid of image analysis and algorithms.

Abstract: This disclosure describes methods, kits, and systems for scoring the immune response to cancer through examination of tissue infiltrating lymphocytes (TILs). Methods of scoring the immune response in cancer using tissue infiltrating lymphocytes include detecting CD3, CD8, CD20, and FoxP3 within the sample and scoring the detection manually or scoring the digital images of the staining with the aid of image analysis and algorithms.

Abstract: The present disclosure is directed to a computer system designed to (i) receive a series of images as input; (ii) compute a number of metrics derived from focus features and color separation features within the images; and (iii) evaluate the metrics to return (a) an identification of the most suitable z-layer in a z-stack, given a series of z-layer images in a z-stack; and/or (b) an identification of those image tiles that are more suitable for cellular based scoring by a medical professional, given a series of image tiles from an area of interest of a whole slide scan.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: The present disclosure is directed to a computer system designed to (i) receive a series of images as input; (ii) compute a number of metrics derived from focus features and color separation features within the images; and (iii) evaluate the metrics to return (a) an identification of the most suitable z-layer in a z-stack, given a series of z-layer images in a z-stack; and/or (b) an identification of those image tiles that are more suitable for cellular based scoring by a medical professional, given a series of image tiles from an area of interest of a whole slide scan.

Abstract: A method and associated method and computer program product for acquiring focused images of a specimen on a slide, by determining optimal scanning trajectories. The method includes capturing a relatively low magnification image of the slide to locate the specimen, forming a grid that includes an arrangement of grid points, overlaying at least part of the grid over a field of view that covers at least part of the specimen, capturing a relatively high magnification Z-stack of images of the specimen within the field of view, determining a best focus for each grid point within said at least part of the grid to form a resulting grid of three dimensional points, and based on the resulting grid, determining one or more three dimensional scanning trajectories.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: A method and associated method and computer program product for acquiring focused images of a specimen on a slide, by determining optimal scanning trajectories. The method includes capturing a relatively low magnification image of the slide to locate the specimen, forming a grid that includes an arrangement of grid points, overlaying at least part of the grid over a field of view that covers at least part of the specimen, capturing a relatively high magnification Z-stack of images of the specimen within the field of view, determining a best focus for each grid point within said at least part of the grid to form a resulting grid of three dimensional points, and based on the resulting grid, determining one or more three dimensional scanning trajectories.

Abstract: The subject disclosure provides systems and methods for determination of Area of Interest (AOI) for different types of input slides. Slide thumbnails may be assigned into one of five different types, and separate algorithms for AOI detection executed depending on the slide type. Slide types include ThinPrep® slides, tissue micro-array (TMA) slides, control HER2 slides with 4 cores, smear slides, and a generic slide. The slide type may be assigned based on a user input. Customized AOI detection operations are provided for each slide type. If the user enters an incorrect slide type, operations include detecting the incorrect input and executing the appropriate method. The result of each AOI detection operations provides as its output a soft-weighted image having zero intensity values at pixels that are detected as not belonging to tissue, and higher intensity values assigned to pixels detected as likely belonging to tissue regions.

Abstract: The present disclosures relates to a method of detecting, classifying, and counting dots in an image of a tissue specimen comprising detecting dots in an image of the tissue sample that meet criteria for absorbance strength, black unmixed image channel strength, red unmixed image channel strength, and a difference of Gaussian threshold, wherein the detected dots correspond to in situ hybridization signals in the tissue samples; classifying the detected dots as belonging to a black in situ hybridization signal or to a red in situ hybridization signal; and calculating a ratio of those dots belonging to the black in situ hybridization signal and those belonging to the red in situ hybridization signal.

Abstract: Techniques are provided for stitching tile images. A local registration can be performed to determine spatial relationships between pairs of adjacent tile images, in which the spatial relationships may be determined using normalized cross correlation (NCC) scores computed within a multi-resolution framework. A global placement can be performed to position all scanned tile images relative to one another. The global placement is determined with weighted least squares utilizing the determined spatial relationships between all adjacent greyscale tile images and the NCC scores as weights.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: The present disclosure describes a method of foreground segmentation and nucleus ranking for scoring dual ISH images. The method has been developed to better identify those nuclei, within a selected field of view, that meet the criteria for dual ISH scoring.

Abstract: The present disclosures relates to a method of detecting, classifying, and counting dots in an image of a tissue specimen comprising detecting dots in an image of the tissue sample that meet criteria for absorbance strength, black unmixed image channel strength, red unmixed image channel strength, and a difference of Gaussian threshold, wherein the detected dots correspond to in situ hybridization signals in the tissue samples; classifying the detected dots as belonging to a black in situ hybridization signal or to a red in situ hybridization signal; and calculating a ratio of those dots belonging to the black in situ hybridization signal and those belonging to the red in situ hybridization signal.