General Electric Company

Ge Healthcare Bio-sciences Corp.

Global Life Sciences Solutions USA LLC

Christopher James Sevinsky

Alberto Santamaria-Pang

Fiona Ginty

Qing Li

Anup Sood

Michael John Gerdes

Zhengyu Pang

Yunxia Sui

Jun Xie

Robert John Filkins

Jens Rittscher

Ali Can

Alex David Corwin

Kashan Ali Shaikh

Brion Daryl Sarachan

Dirk Ryan Padfield

Colin Craig McCulloch

Dmitry Vladimirovich Dylov

Yousef Ahmed Al-Kofahi

Michael Ernest Marino

Musodiq O Bello

Daniel Eugene Meyer

Megan Pearl Rothney

Srabani Bhaumik

Raghav Krishna Padmanabhan

Keyur Hemantkumar Desai

Jingyu Zhang

Nicole Evelyn LaPlante

Colin Craig Mcculloch

Fiona Mary Ginty

The subject matter of the present disclosure generally relates to techniques for image analysis. In certain embodiments, various morphological or intensity-based features as well as different thresholding approaches may be used to segment the subpopulation of interest and classify object in the images.

Systems and methods for automatic generation of training sets for machine interpretation of images

Disclosed are novel computer-implemented methods for creating a blood vessel map of a biological tissue. The methods comprise the steps of, accessing image data corresponding to multi-channel multiplexed image of a fluorescently stained biological tissue manifesting expression levels of a primary marker and at least one auxiliary marker of blood vasculature, and extracting features of blood vessels using the primary marker as an input to create a single channel segmentation of the blood vessels. The method further comprises the steps of extracting features of blood vessels using the auxiliary marker to create auxiliary channels as a second input and apply multi-channel blood vessel enhancement. Blood vessel maps are created using the features and tracing the blood vasculature by iteratively extending the centerlines of the initial segmentation using statistical models and geometric rules.

System and method for blood vessel analysis and quantification in highly multiplexed fluorescence imaging

The disclosed embodiments are directed to a method for accurately counting and characterizing multiple cell phenotypes and sub-phenotypes within cell populations simultaneously by exploiting biomarker co-expression levels within cells of different phenotypes in the same tissue sample. The disclosed embodiments are also directed to a simple intuitive interface enabling medical staff (e.g., pathologists, biologists) to annotate and evaluate different cell phenotypes used in the algorithm and the presented through the interface.

Method and system for classification and quantitative analysis of cell types in microscopy images

The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a distribution, location, and type of a plurality of the characterized cells.

Quantitative in situ characterization of biological samples

Improved systems and methods for the analysis of digital images are provided. More particularly, the present disclosure provides for improved systems and methods for the analysis of digital images of biological tissue samples. Exemplary embodiments provide for: i) segmenting, ii) grouping, and iii) quantifying molecular protein profiles of individual cells in terms of sub cellular compartments (nuclei, membrane, and cytoplasm). The systems and methods of the present disclosure advantageously perform tissue segmentation at the sub-cellular level to facilitate analyzing, grouping and quantifying protein expression profiles of tissue in tissue sections globally and/or locally. Performing local-global tissue analysis and protein quantification advantageously enables correlation of spatial and molecular configuration of cells with molecular information of different types of cancer.

System and method for multiplexed biomarker quantitation using single cell segmentation on sequentially stained tissue

Exemplary embodiments enable determination of spatial proximity between two or more features in biological tissue. An exemplary method includes identifying a morphological feature in an image of the biological tissue based on expression levels of a first biomarker indicative of the morphological feature, and receiving a result of a segmentation analysis performed on the image of the biological tissue identifying a set of morphological units in the image external to the morphological feature. An exemplary method includes determining an expression level of a second biomarker corresponding to each unit in the set of morphological units in the image of the biological tissue, and determining a spatial distance between the morphological feature and each unit in the set of morphological units. An exemplary method further includes automatically determining a relationship between expression levels of the second biomarker and corresponding spatial distance from the morphological feature of the set of morphological units.

Determination of spatial proximity between features of interest in biological tissue

A closed loop automated method for staining of a biological sample is provided. The method comprises providing a biological sample, staining at least a portion of the biological sample by flowing in a reagent, monitoring one or more optical characteristics of the biological sample, and calculating a figure of merit based on at least one of the optical characteristics. An automated device for iterative staining of a biological sample is also provided.

Closed loop monitoring of automated molecular pathology system

The invention provides a method for antigen retrieval of a formaldehyde-fixed tissue sample comprising incubating a formaldehyde-fixed tissue sample in a first antigen retrieval solution at a temperature of greater than 90&#xb0; C., transferring the tissue sample to a second antigen retrieval solution, and incubating the tissue sample in the second antigen retrieval solution at a temperature of greater than 90&#xb0; C. The invention also provides a kit and sample delivery device for carrying out the method.

Method and apparatus for antigen retrieval process

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Watervliet, NY, United States of America

Christopher James Sevinsky