公开(公告)号：US12182996B2

公开(公告)日：2024-12-31

申请号：US17591640

申请日：2022-02-03

Applicant: PAIGE.AI, Inc.

Inventor： Danielle Gorton ,  Matthew Hanna ,  Christopher Kanan

IPC: G06T7/00

Abstract: A computer-implemented method may identify attributes of electronic images and display the attributes. The method may include receiving one or more electronic medical images associated with a pathology specimen, determining a plurality of salient regions within the one or more electronic medical images, determining a predetermined order of the plurality of salient regions, and automatically panning, using a display, across the one or more salient regions according to the predetermined order.

公开(公告)号：US11710235B2

公开(公告)日：2023-07-25

申请号：US17552438

申请日：2021-12-16

Applicant: PAIGE.AI, Inc.

Inventor： Danielle Gorton ,  Patricia Raciti ,  Jillian Sue ,  Razik Yousfi

IPC: G06K9/00 ,  G06T7/00 ,  G06V10/25 ,  G06V10/12 ,  G06V10/77 ,  G16H10/40 ,  G16H15/00 ,  G16H50/20 ,  G16H30/40 ,  G16H80/00 ,  G06T11/60

CPC classification number: G06T7/0014 ,  G06T11/60 ,  G06V10/12 ,  G06V10/25 ,  G06V10/7715 ,  G16H10/40 ,  G16H15/00 ,  G16H30/40 ,  G16H50/20 ,  G16H80/00 ,  G06T2207/10004 ,  G06T2207/30004 ,  G06T2207/30024 ,  G06V2201/03

Abstract: A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

公开(公告)号：US12094118B2

公开(公告)日：2024-09-17

申请号：US18329024

申请日：2023-06-05

Applicant: PAIGE.AI, Inc.

Inventor： Danielle Gorton ,  Patricia Raciti ,  Jillian Sue ,  Razik Yousfi

IPC: G06K9/00 ,  G06T7/00 ,  G06T11/60 ,  G06V10/12 ,  G06V10/25 ,  G06V10/77 ,  G16H10/40 ,  G16H15/00 ,  G16H30/40 ,  G16H50/20 ,  G16H80/00

CPC classification number: G06T7/0014 ,  G06T11/60 ,  G06V10/12 ,  G06V10/25 ,  G06V10/7715 ,  G16H10/40 ,  G16H15/00 ,  G16H30/40 ,  G16H50/20 ,  G16H80/00 ,  G06T2207/10004 ,  G06T2207/30004 ,  G06T2207/30024 ,  G06V2201/03

Abstract: A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

公开(公告)号：US11538162B2

公开(公告)日：2022-12-27

申请号：US17565681

申请日：2021-12-30

Applicant: PAIGE.AI, Inc.

Inventor： Danielle Gorton ,  Patricia Raciti ,  Jillian Sue ,  Razik Yousfi

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/12 ,  G06V10/77 ,  G16H10/40 ,  G16H15/00 ,  G16H50/20 ,  G16H30/40 ,  G16H80/00 ,  G06T11/60

Abstract: A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.