Icahn School of Medicine at Mount Sinai

Fundacao D. Anna Sommer Champalimaud E Dr. Carlos Montez Champalimaud

Hoffmann-la Roche Inc.

Ventana Medical Systems, Inc.

Fundação D. Anna De Sommer Champalimaud E Dr. Carlos Montez Champalimaud

F. Hoffmann-la Roche Ag

Gerardo Fernandez

Marcel Prastawa

Jack Zeineh

Michael Donovan

Faisal Khan

Peter Ajemba

Qiuhua Liu

Richard Jonathan Scott

Janakiramanan Ramachandran

Carlos Cordon-Cardo

Ricardo Mesa-Tejada

Jose Costa

Carlos Cardon-Cardo

Srinivas Chukka

Quan Yuan

Elizabeth Little

Stefan Hamann

Angelika Fuchs

Stephen Fogarasi

Yevgen Vengrenyuk

Jason Alter

Douglas Powell

Valentina Bayer Zubek

Ali Tabesh

Douglas A Powell

Richard Scott

Systems and methods to train a cell object detector are described.

Systems and methods to train a cell object detector

Display screen with a graphical user interface

Systems and methods to label structures of interest in tissue slide images are described.

Systems and methods to label structures of interest in tissue slide images

Systems and methods for analyzing vessels in multiplexed images include detecting large vessels using a spoke feature detection method, detecting long and narrow vessels using a line feature detection method, detecting smaller vessels using rolling-ball filtering and binary image operations to generate a mask, and evaluating any contour polygons resulting from these operations using quality measurements and other thresholds. Maturity determination and nuclei detection are also performed, resulting in an output of vessel characteristics and co-locations enabling enhanced analysis of multispectral images.

Vessel analysis in multiplexed images

Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Systems and methods for segmentation and processing of tissue images and feature extraction from same for treating, diagnosing, or predicting medical conditions

Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.

Method and system for determining the risk of occurrence of prostate cancer

Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g., multiplex immunofluorescence (IF)) performance and/or to normalize features for use within a predictive model.

System for evaluating a pathological stage of prostate cancer

Growing community of inventors

New York, NY, United States of America

Gerardo Fernandez