公开(公告)号：US12148532B2

公开(公告)日：2024-11-19

申请号：US18150491

申请日：2023-01-05

Applicant: PAIGE.AI, Inc.

Inventor： Jillian Sue ,  Thomas Fuchs ,  Christopher Kanan

IPC: G16H50/20 ,  G06F18/2113 ,  G06F18/214 ,  G06T7/00 ,  G16H30/20

Abstract: Systems and methods are disclosed for identifying a diagnostic feature of a digitized pathology image, including receiving one or more digitized images of a pathology specimen, and medical metadata comprising at least one of image metadata, specimen metadata, clinical information, and/or patient information, applying a machine learning model to predict a plurality of relevant diagnostic features based on medical metadata, the machine learning model having been developed using an archive of processed images and prospective patient data, and determining at least one relevant diagnostic feature of the relevant diagnostic features for output to a display.

公开(公告)号：US12131473B2

公开(公告)日：2024-10-29

申请号：US18523098

申请日：2023-11-29

Applicant: PAIGE.AI, Inc.

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

IPC: G06T7/00 ,  G06F18/214 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06F18/214 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V2201/03

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：US11869185B2

公开(公告)日：2024-01-09

申请号：US17804123

申请日：2022-05-26

Applicant: PAIGE.AI, Inc.

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

IPC: G06T7/00 ,  G16H50/20 ,  G16H30/40 ,  G06F18/214

CPC classification number: G06T7/0012 ,  G06F18/214 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V2201/03

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：US11823378B2

公开(公告)日：2023-11-21

申请号：US17107433

申请日：2020-11-30

Applicant: PAIGE.AI, Inc.

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

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

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T7/194 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06V10/993 ,  G06V20/69 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06V2201/03

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：US11494907B2

公开(公告)日：2022-11-08

申请号：US17123658

申请日：2020-12-16

Applicant: PAIGE.AI, Inc.

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

IPC: G06T7/00 ,  G06T7/11 ,  G06V20/69

Abstract: Systems and methods are disclosed for receiving a digital image corresponding to a target specimen associated with a pathology category, wherein the digital image is an image of tissue specimen, determining a detection machine learning model, the detection machine learning model being generated by processing a plurality of training images to output a cancer qualification and further a cancer quantification if the cancer qualification is an confirmed cancer qualification, providing the digital image as an input to the detection machine learning model, receiving one of a pathological complete response (pCR) cancer qualification or a confirmed cancer quantification as an output from the detection machine learning model, and outputting the pCR cancer qualification or the confirmed cancer quantification.

公开(公告)号：US11481898B2

公开(公告)日：2022-10-25

申请号：US17519106

申请日：2021-11-04

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：US11475566B2

公开(公告)日：2022-10-18

申请号：US17410031

申请日：2021-08-24

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：US11227684B2

公开(公告)日：2022-01-18

申请号：US17119885

申请日：2020-12-11

Applicant: PAIGE.AI, Inc.

Inventor： Christopher Kanan ,  Rodrigo Ceballos Lentini ,  Jillian Sue ,  Thomas Fuchs ,  Leo Grady

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

Abstract: Systems and methods are disclosed for determining at least one geographic region of a plurality of geographic regions, at least one data variable, and/or at least one health variable, estimating a current prevalence of a data variable in a geographic region of the plurality of geographic regions, determining a trend in a relationship between the data variable and the geographic region at a current time, determining a second trend in the relationship between the data variable and the geographic region at at least one prior point in time, determining if the trend in the relationship is irregular within a predetermined threshold with respect to the second trend from the at least one prior point in time, and, upon determining that the trend in the relationship is irregular within a predetermined threshold, generating an alert.

公开(公告)号：US11995903B2

公开(公告)日：2024-05-28

申请号：US18186252

申请日：2023-03-20

Applicant: PAIGE.AI, Inc.

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

IPC: G06V20/69 ,  G06F18/214 ,  G06N20/00 ,  G06T7/00 ,  G06T7/136 ,  G06T7/194 ,  G06V10/26 ,  G06V10/28

CPC classification number: G06V20/695 ,  G06F18/2155 ,  G06N20/00 ,  G06T7/0012 ,  G06T7/136 ,  G06T7/194 ,  G06V10/26 ,  G06V10/28 ,  G06V20/698 ,  G06T2207/20081 ,  G06T2207/30024

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：US11928820B2

公开(公告)日：2024-03-12

申请号：US18174284

申请日：2023-02-24

Applicant: PAIGE.AI, Inc.

Inventor： Jillian Sue ,  Razik Yousfi ,  Peter Schueffler ,  Thomas Fuchs ,  Leo Grady

IPC: G06K9/00 ,  G06T7/00 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60

CPC classification number: G06T7/0014 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T2207/30168

Abstract: Systems and methods are disclosed for receiving a digital image corresponding to a target specimen associated with a pathology category, determining a quality control (QC) machine learning model to predict a quality designation based on one or more artifacts, providing the digital image as an input to the QC machine learning model, receiving the quality designation for the digital image as an output from the machine learning model, and outputting the quality designation of the digital image. A quality assurance (QA) machine learning model may predict a disease designation based on one or more biomarkers. The digital image may be provided to the QA model which may output a disease designation. An external designation may be compared to the disease designation and a comparison result may be output.