General Electric Company

Ge Healthcare Bio-sciences Corp.

Other

Global Life Sciences Solutions USA LLC

Brion Daryl Sarachan

John Frederick Graf

Alberto Santamaria-Pang

Vidya Pundalik Kamath

Megan Pearl Rothney

Yousef Ahmed Al-Kofahi

Qing Li

Michael John Gerdes

Jens Rittscher

Colin Craig McCulloch

Fiona Ginty

Christopher Reynolds Hammond

Zhengyu Pang

Raghav Krishna Padmanabhan

Edward John Moler

Anup Sood

Ali Can

Matthew David Kelly

Brian Michael Davis

Faisal Ahmed Syud

Kevin Bernard Kenny

Dirk Ryan Padfield

Musodiq O Bello

Christopher James Sevinsky

Michael Adam Kinstrey

David LaVan Henderson

Thomas Paul Repoff

John Michael Brady

David Kerr

Helena Goldfarb

Stephen John Angelovich

Mary Elizabeth Spilker

Ralph Andrew Minerva

John Espirito Santo Amaral

Alexandra Jay Schmidt

Mary Kathleen Callahan

Rachel Susannah Midgley

Mark Robert Austin

Fiona Mary Ginty

Identification of regions-of-interest within cell maps is disclosed. In certain embodiments, identification of the regions-of interest is based on the use of biomarkers selected based on nucleic acid sequence data. The nucleic acid sequence data may be acquired for a homogeneous or heterogeneous set of cells present in the respective tissue sample.

Biological data annotation and visualization

The disclosed subject matter relates to an automated determination of cell-by-cell segmentation quality of a tissue specimen sample. A training set of cells is examined by an expert to determine which cells that include 'good' segmentation and which cells include 'poor' segmentation. A training model is build based on the image data of the cells in the training set. Image data from cells in a test specimen is obtained and that image data is compared to the training model to determine on a cell-by-cell basis which cells in the test specimen include &#x201c;good&#x201d; segmentation and which cells include &#x201c;poor&#x201d; segmentation. The accumulated data on the cells analyzed in the test specimen can be utilized to determine an overall segmentation quality score for the area of the test specimen in which the individual cells are located in the test specimen.

Automated cell segmentation quality control

Identification of regions-of-interest within cell maps is disclosed. In certain embodiments, identification of the regions-of interest is based on the use of a plurality of biomarkers, which may be used to generate a multiplexed image of a tissue sample. Based on the identified regions, cells may be extracted and localized sequence data may be generated specific to the regions-of-interest.

The present disclosure relates to characterization of biological samples via modular image analysis. By way of example, the analysis may include extracting plurality of regions of interest from the biological sample from a plurality of image data sets. Each region of interest may include a combination of one or more subsets of an image data set. In one example, an image data set may be generated by image segmentation. After each region of interest is extracted, at least one metric of the region of interest may be determined.

Modular image analysis system and method

The disclosed subject matter relates to an automated determination the stain quality and segmentation quality of a tissue sample. By way of example, separate image data is acquired of an unstained form of a biological specimen, the biological specimen stained with a nuclei marker and the biological specimen stained with a segmentation marker. A correlation map (Cr) from the separate image data and a ridgeness map (Pr) from the image data of the biological specimen stained with a segmentation marker are each determined. A staining quality score and segmentation quality score are then determined from the correlation map (Cr) and the ridgeness map (Pr).

Automated staining and segmentation quality control

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 heterogeneity of the characterized cells.

Quantitative in situ characterization of heterogeneity in biological samples

Dynamic linking of pathway maps and cell maps is disclosed in certain embodiments. In such embodiments, the pathway maps are linked to spatially-localized regional nucleic acid data (e.g., sequence data), as opposed to non-spatially selected nucleic acid data. The pathway map and cell map data may be linked so that interactions results in changes or updates to the linked map, such as the selection or highlighting of cells exhibiting pathway map characteristics specified by a user of updating of node values or states to correspond to that of a cell or cells selected by the user.

Exemplary embodiments include methods, systems, and devices for enabling users to provide quality scores for indicating the quality of image analysis methods performed on images of biological tissue. An exemplary user interface displays results of an image analysis method performed on an image of biological tissue in an overlaid manner on an image of biological tissue. The exemplary user interface enable a user to provide, directly on the user interface, one or more quality scores to indicate the user's assessment of the quality of the image analysis performed on the image. Exemplary embodiments store the quality scores provided by the user in association with the image analysis method and the image of biological tissue.

Systems and methods for performing quality review scoring of biomarkers and image analysis methods for biological tissue

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

The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in an individual cell wherein the cell is examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Process and system for analyzing the expression of biomarkers in a cell

Embodiments disclosed herein include methods, systems, and devices for determining a positive or negative correlation between a clinical outcome and one or more features of biological tissue. An exemplary user interface enables a user to select a clinical outcome and one or more aspects of a displayed field-of-view of biological tissue. Exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of the user-selected aspects of the field-of-view of biological tissue. For example, exemplary embodiments may automatically perform correlation analysis between the selected clinical outcome and one or more features characteristic of one or more biological units in the biological tissue.

Systems and methods for performing correlation analysis on clinical outcome and characteristics of biological tissue

The quantitative evaluation of biomarker-probe activity is disclosed. In certain embodiments, the biomarker-probe activity may be quantified and analyzed using biodistributions generated using a model. In some embodiments, such biodistributions may be used to generate simulated images from which quantitative thresholds may be derived. In some embodiments, the quantitative thresholds may be used to analyze the biodistributions.

Method and apparatus for assessing feasibility of probes and biomarkers

A method and system are provided for facilitating decision making, such as in a clinical setting. In accordance with this technique, a set of encoded guidelines are executed to identify information that may be used to generate patient management options. The information is acquired, if available. Based on the encoded guidelines and the acquired information, a set of patient management options are generated and provided to one or more reviewers for review and selection of a patient management option.

Method and system for supporting clinical decision-making

The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in individual cells wherein the cells are examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Process and system for analyzing the expression of biomarkers in cells

An Integration Controller integrates broadcast automation systems and thereby provides a single command and control center for monitoring production of the audio and video stream. An event-based schedule, or a &ldquo;playlist,&rdquo; specifies the segments to be played along with the necessary timing and hardware information. Each event in the schedule commands the playback or record of a video segment, generation of a special effect, transfer of a video segment from one device to another or closure of one or more video switches. Events may be launched automatically at a specified time, or manually by an operator. An Integration Controller (IC) communicates with an Event Scheduling System via a Scheduling System Interface. The Scheduling System Interface communicates with the Integration Controller via the IC server. The IC server utilizes various modules to communicate with Device Drivers, a Log Manager and one or more User Interfaces.

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Schenectady, NY, United States of America

Brion Daryl Sarachan