公开(公告)号：US11823436B2

公开(公告)日：2023-11-21

申请号：US17710613

申请日：2022-03-31

Applicant: PAIGE.AI, Inc.

Inventor： Belma Dogdas ,  Christopher Kanan ,  Thomas Fuchs ,  Leo Grady

IPC: G06V10/764 ,  G16H50/20 ,  G16H30/40 ,  G06T7/00 ,  G06V10/82 ,  G06V20/69

CPC classification number: G06V10/764 ,  G06T7/0012 ,  G06V10/82 ,  G06V20/698 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096

Abstract: Systems and methods are disclosed for generating a specialized machine learning model by receiving a generalized machine learning model generated by processing a plurality of first training images to predict at least one cancer characteristic, receiving a plurality of second training images, the first training images and the second training images include images of tissue specimens and/or images algorithmically generated to replicate tissue specimens, receiving a plurality of target specialized attributes related to a respective second training image of the plurality of second training images, generating a specialized machine learning model by modifying the generalized machine learning model based on the plurality of second training images and the target specialized attributes, receiving a target image corresponding to a target specimen, applying the specialized machine learning model to the target image to determine at least one characteristic of the target image, and outputting the characteristic of the target image.

公开(公告)号：US11508066B2

公开(公告)日：2022-11-22

申请号：US17399422

申请日：2021-08-11

Applicant: PAIGE.AI, Inc.

Inventor： Christopher Kanan ,  Belma Dogdas ,  Patricia Raciti ,  Matthew Lee ,  Alican Bozkurt ,  Leo Grady ,  Thomas Fuchs ,  Jorge S. Reis-Filho

IPC: G06T7/00 ,  G06T7/11 ,  G16H50/20 ,  G16H30/40 ,  G06V10/46 ,  G06K9/62 ,  G16H10/60 ,  G06N20/00

Abstract: Systems and methods are disclosed for processing digital images to predict at least one continuous value comprising receiving one or more digital medical images, determining whether the one or more digital medical images includes at least one salient region, upon determining that the one or more digital medical images includes the at least one salient region, predicting, by a trained machine learning system, at least one continuous value corresponding to the at least one salient region, and outputting the at least one continuous value to an electronic storage device and/or display.

公开(公告)号：US11475990B2

公开(公告)日：2022-10-18

申请号：US17160129

申请日：2021-01-27

Applicant: PAIGE.AI, Inc.

Inventor： Jillian Sue ,  Jason Locke ,  Peter Schueffler ,  Christopher Kanan ,  Thomas Fuchs ,  Leo Grady

IPC: G16H30/20 ,  G06N20/00

Abstract: Systems and methods are disclosed for receiving one or more digital images associated with a tissue specimen, a related case, a patient, and/or a plurality of clinical information, determining one or more of a prediction, a recommendation, and/or a plurality of data for the one or more digital images using a machine learning system, the machine learning system having been trained using a plurality of training images, to predict a biomarker and a plurality of genomic panel elements, and determining, based on the prediction, the recommendation, and/or the plurality of data, whether to log an output and at least one visualization region as part of a case history within a clinical reporting system.

公开(公告)号：US11182900B2

公开(公告)日：2021-11-23

申请号：US17160127

申请日：2021-01-27

Applicant: PAIGE.AI, Inc.

Inventor： Belma Dogdas ,  Christopher Kanan ,  Thomas Fuchs ,  Leo Grady

IPC: G06T7/00 ,  G16H10/40

Abstract: Systems and methods are disclosed for receiving digital images of a pathology specimen from a patient, the pathology specimen comprising tumor tissue, the one or more digital images being associated with data about a plurality of biomarkers in the tumor tissue and data about a surrounding invasive margin around the tumor tissue; identifying the tumor tissue and the surrounding invasive margin region to be analyzed for each of the one or more digital images; generating, using a machine learning model on the one or more digital images, at least one inference of a presence of the plurality of biomarkers in the tumor tissue and the surrounding invasive margin region; determining a spatial relationship of each of the plurality of biomarkers identified in the tumor tissue and the surrounding invasive margin region to themselves and to other cell types; and determining a prediction for a treatment outcome and/or at least one treatment recommendation for the patient.

公开(公告)号：US11062801B2

公开(公告)日：2021-07-13

申请号：US17137769

申请日：2020-12-30

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo Ceballos Lentini ,  Christopher Kanan ,  Patricia Raciti ,  Leo Grady ,  Thomas Fuchs

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

Abstract: Systems and methods are disclosed for processing an electronic image corresponding to a specimen. One method for processing the electronic image includes: receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample from a patient, applying a machine learning system to the target electronic image to determine deficiencies associated with the target specimen, the machine learning system having been generated by processing a plurality of training images to predict stain deficiencies and/or predict a needed recut, the training images including images of human tissue and/or images that are algorithmically generated; and based on the deficiencies associated with the target specimen, determining to automatically order an additional slide to be prepared.

公开(公告)号：US10937541B2

公开(公告)日：2021-03-02

申请号：US16884978

申请日：2020-05-27

Applicant: PAIGE.AI, Inc.

Inventor： Rodrigo Ceballos Lentini ,  Christopher Kanan ,  Patricia Raciti ,  Leo Grady ,  Thomas Fuchs

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

Abstract: Systems and methods are disclosed for processing an electronic image corresponding to a specimen. One method for processing the electronic image includes: receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample from a patient, applying a machine learning system to the target electronic image to determine deficiencies associated with the target specimen, the machine learning system having been generated by processing a plurality of training images to predict stain deficiencies and/or predict a needed recut, the training images including images of human tissue and/or images that are algorithmically generated; and based on the deficiencies associated with the target specimen, determining to automatically order an additional slide to be prepared.

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：US11776681B2

公开(公告)日：2023-10-03

申请号：US17809313

申请日：2022-06-28

Applicant: PAIGE.AI, Inc.

Inventor： Ran Godrich ,  Jillian Sue ,  Leo Grady ,  Thomas Fuchs

IPC: G06T7/00 ,  G06N20/00 ,  G16H50/20 ,  G16H70/60 ,  G16H40/20 ,  G16H10/40 ,  G16H30/40 ,  G16H70/20 ,  G16B40/20 ,  G06K9/62 ,  G06F18/214

CPC classification number: G16H30/40 ,  G06F18/214 ,  G06N20/00 ,  G06T7/0012 ,  G16B40/20 ,  G16H10/40 ,  G16H40/20 ,  G16H50/20 ,  G16H70/20 ,  G16H70/60 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06T2207/30204 ,  G06V2201/03 ,  G06V2201/04

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