公开(公告)号：US20220375573A1

公开(公告)日：2022-11-24

申请号：US17646500

申请日：2021-12-30

Applicant: PAIGE.AI, Inc.

Inventor： Ran GODRICH ,  Christopher KANAN

IPC: G16H30/20 ,  G06N20/00

Abstract: Systems and methods are disclosed for identifying tissue specimen types present in digital whole slide images. In some aspects, tissue specimen types may be identified using unsupervised machine learning techniques for out-of-distribution detection. For example, a digital whole slide image of a tissue specimen and a recorded tissue specimen type for the digital whole slide image may be received. One or more feature vectors may be extracted from one or more foreground tiles of the digital whole slide image identified as including the tissue specimen, and a distribution learned by a machine learning system for the recorded tissue specimen type may be received. Using the distribution, a probability of the feature vectors corresponding to the recorded tissue specimen type may be computed and used as a basis for classifying the foreground tiles from which the feature vectors are extracted as an in-distribution foreground tile or an out-of-distribution foreground tile.

公开(公告)号：US20220335607A1

公开(公告)日：2022-10-20

申请号：US17810815

申请日：2022-07-05

Applicant: PAIGE.AI, Inc.

Inventor： Supriya KAPUR ,  Ran GODRICH ,  Christopher KANAN ,  Thomas FUCHS ,  Leo GRADY

IPC: G06T7/00 ,  G06T7/11 ,  G16H10/40 ,  G16H50/20 ,  G16H30/40 ,  G06K9/62 ,  G06V10/20 ,  G06V20/69

Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.

公开(公告)号：US20220012880A1

公开(公告)日：2022-01-13

申请号：US17377260

申请日：2021-07-15

Applicant: PAIGE.AI, Inc.

Inventor： Ran GODRICH ,  Jillian SUE ,  Leo GRADY ,  Thomas FUCHS

IPC: G06T7/00 ,  G06N20/00 ,  G16H50/20

Abstract: An image processing method including receiving a target image of a slide corresponding to a target specimen comprising a tissue sample of a patient; generating a machine learning system by processing a plurality of training images, each training image comprising an image of human tissue and a label characterizing at least one of a slide morphology, a diagnostic value, a pathologist review outcome, and an analytic difficulty; automatically identifying, using the machine learning system, an area of interest of the target image by analyzing microscopic features extracted from multiple image regions in the target image; determining, using the machine learning system, a probability of a target feature being present in the area of interest of the target image based on an average probability; and determining, using the machine learning system, a prioritization value, of a plurality of prioritization values.

公开(公告)号：US20210073986A1

公开(公告)日：2021-03-11

申请号：US17016048

申请日：2020-09-09

Applicant: PAIGE.AI, Inc.

Inventor： Supriya KAPUR ,  Ran GODRICH ,  Christopher KANAN ,  Thomas FUCHS ,  Leo GRADY

IPC: G06T7/00 ,  G06K9/32 ,  G06K9/62 ,  G06K9/00 ,  G06T7/11 ,  G16H10/40 ,  G16H50/20 ,  G16H30/40

Abstract: Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.

公开(公告)号：US20200381122A1

公开(公告)日：2020-12-03

申请号：US16887855

申请日：2020-05-29

Applicant: PAIGE.AI, Inc.

Inventor： Ran GODRICH ,  Jillian SUE ,  Leo GRADY ,  Thomas FUCHS

IPC: G16H50/20 ,  G06K9/62 ,  G16H30/40 ,  G16H10/40 ,  G16H70/60 ,  G16H70/20 ,  G16H40/20 ,  G16B40/20

Abstract: Systems and methods are disclosed for processing an electronic image corresponding to a specimen and automatically prioritizing processing of the electronic image. One method includes receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample of a patient; computing, using a machine learning system, a prioritization value of the target electronic image, the machine learning system having been generated by processing a plurality of training images, each training image comprising an image of human tissue and a label characterizing at least one of a slide morphology, a diagnostic value, a pathologist review outcome, and/or an analytic difficulty; and outputting a sequence of digitized pathology images, wherein a placement of the target electronic image in the sequence is based on the prioritization value of the target electronic image.