公开(公告)号：US12266096B2

公开(公告)日：2025-04-01

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 ,  G06F18/214 ,  G06T7/11 ,  G06V20/69 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20

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：US12217423B2

公开(公告)日：2025-02-04

申请号：US18487264

申请日：2023-10-16

Applicant: PAIGE.AI, Inc.

Inventor： Patricia Raciti ,  Christopher Kanan ,  Thomas Fuchs ,  Leo Grady

IPC: G06T7/194 ,  G06T7/00 ,  G06T7/11 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06V10/98 ,  G06V20/69

Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, detecting one or more image regions from a background of the one or more digital images, determining a prediction, using a machine learning system, of whether at least one first image region of the one or more image regions comprises at least one external contaminant, the machine learning system having been trained using a plurality of training images to predict a presence of external contaminants and/or a location of any external contaminants present in the tissue specimen, and determining, based on the prediction of whether a first image region comprises an external contaminant, whether to process the image region using an processing algorithm.

公开(公告)号：US12148159B2

公开(公告)日：2024-11-19

申请号：US18530844

申请日：2023-12-06

Applicant: PAIGE.AI, Inc.

Inventor： Jason Locke ,  Jillian Sue ,  Christopher Kanan ,  Sese Ih

IPC: G06K9/00 ,  A61B6/00 ,  G06N20/00 ,  G06T3/40 ,  G06T7/00 ,  G06T11/60 ,  G16H10/40 ,  G16H30/40 ,  G16H70/60

Abstract: Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type; determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.

公开(公告)号：US12131817B2

公开(公告)日：2024-10-29

申请号：US18045907

申请日：2022-10-12

Applicant: PAIGE.AI, Inc.

Inventor： Leo Grady ,  Christopher Kanan ,  Jorge S. Reis-Filho

IPC: G16H20/40 ,  A61N5/10 ,  G06N20/00 ,  G06T7/00 ,  G06V10/25 ,  G16H50/30

CPC classification number: G16H20/40 ,  A61N5/103 ,  G06N20/00 ,  G06T7/0012 ,  G06V10/25 ,  G16H50/30 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096

Abstract: Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.

公开(公告)号：US11887304B2

公开(公告)日：2024-01-30

申请号：US17655524

申请日：2022-03-18

Applicant: PAIGE.AI, Inc.

Inventor： Jason Locke ,  Jillian Sue ,  Christopher Kanan ,  Sese Ih

IPC: G06K9/00 ,  A61B6/00 ,  G06T7/00 ,  G16H70/60 ,  G16H10/40 ,  G16H30/40 ,  G06N20/00 ,  G06T3/40 ,  G06T11/60

CPC classification number: G06T7/0012 ,  G06N20/00 ,  G06T3/40 ,  G06T11/60 ,  G16H10/40 ,  G16H30/40 ,  G16H70/60 ,  G06T2207/20081 ,  G06T2207/30024

Abstract: Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type; determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.

公开(公告)号：US11640719B2

公开(公告)日：2023-05-02

申请号：US17811960

申请日：2022-07-12

Applicant: PAIGE.AI, Inc.

Inventor： Brandon Rothrock ,  Christopher Kanan ,  Julian Viret ,  Thomas Fuchs ,  Leo Grady

IPC: G06T7/136 ,  G06T7/194 ,  G06T7/00 ,  G06N20/00 ,  G06K9/62

Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.

公开(公告)号：US11501869B2

公开(公告)日：2022-11-15

申请号：US17493917

申请日：2021-10-05

Applicant: PAIGE.AI, Inc.

Inventor： Leo Grady ,  Christopher Kanan ,  Jorge S. Reis-Filho

IPC: G16H20/40 ,  G06T7/00 ,  G06N20/00 ,  G06V10/25 ,  G16H50/30 ,  A61N5/10

Abstract: Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.

公开(公告)号：US11482319B2

公开(公告)日：2022-10-25

申请号：US17457451

申请日：2021-12-03

Applicant: PAIGE.AI, INC.

Inventor： Patricia Raciti ,  Christopher Kanan ,  Alican Bozkurt ,  Belma Dogdas

IPC: G16H30/20 ,  G06T7/00 ,  G06T11/00 ,  G06V10/77

Abstract: A computer-implemented method may include receiving a collection of unstained digital histopathology slide images at a storage device and running a trained machine learning model on one or more slide images of the collection to infer a presence or an absence of a salient feature. The trained machine learning model may have been trained by processing a second collection of unstained or stained digital histopathology slide images and at least one synoptic annotation for one or more unstained or stained digital histopathology slide images of the second collection. The computer-implemented method may further include determining at least one map from output of the trained machine learning model and providing an output from the trained machine learning model to the storage device.

公开(公告)号：US11482317B2

公开(公告)日：2022-10-25

申请号：US17486371

申请日：2021-09-27

Applicant: PAIGE.AI, Inc.

Inventor： Leo Grady ,  Christopher Kanan ,  Jorge S. Reis-Filho

IPC: G16H20/40 ,  G06T7/00 ,  G06N20/00 ,  A61N5/10 ,  G16H50/30 ,  G06V10/25

Abstract: Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.

公开(公告)号：US11423547B2

公开(公告)日：2022-08-23

申请号：US17480826

申请日：2021-09-21

Applicant: PAIGE.AI, Inc.

Inventor： Brandon Rothrock ,  Christopher Kanan ,  Julian Viret ,  Thomas Fuchs ,  Leo Grady

IPC: G06T7/136 ,  G06T7/194 ,  G06T7/00 ,  G06N20/00 ,  G06K9/62

Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.