US 11,995,903 B2
Systems and methods for processing electronic images for computational detection methods
Brandon Rothrock, Los Angeles, CA (US); Christopher Kanan, Pittsford, NY (US); Julian Viret, New York, NY (US); Thomas Fuchs, New York, NY (US); and Leo Grady, Darien, CT (US)
Assigned to Paige.AI, Inc., New York, NY (US)
Filed by PAIGE.AI, Inc., New York, NY (US)
Filed on Mar. 20, 2023, as Appl. No. 18/186,252.
Application 18/186,252 is a continuation of application No. 17/811,960, filed on Jul. 12, 2022, granted, now 11,640,719.
Application 17/811,960 is a continuation of application No. 17/480,826, filed on Sep. 21, 2021, granted, now 11,423,547, issued on Aug. 23, 2022.
Application 17/480,826 is a continuation of application No. 17/159,849, filed on Jan. 27, 2021, granted, now 11,176,676, issued on Nov. 16, 2021.
Claims priority of provisional application 62/966,716, filed on Jan. 28, 2020.
Prior Publication US 2023/0245477 A1, Aug. 3, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 20/69 (2022.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06T 7/00 (2017.01); G06T 7/136 (2017.01); G06T 7/194 (2017.01); G06V 10/26 (2022.01); G06V 10/28 (2022.01)
CPC G06V 20/695 (2022.01) [G06F 18/2155 (2023.01); G06N 20/00 (2019.01); G06T 7/0012 (2013.01); G06T 7/136 (2017.01); G06T 7/194 (2017.01); G06V 10/26 (2022.01); G06V 10/28 (2022.01); G06V 20/698 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for processing electronic slide images, the method comprising:
receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case;
generating a machine learning prediction model by:
partitioning one of a plurality of training images into a plurality of training tiles for the plurality of training images;
creating a training tissue mask by detecting at least one tissue region from a background of the one or more electronic slide images;
removing at least one of the plurality of tiles detected to be non-tissue; and
using the machine learning prediction model under weak supervision to infer at least one tile-level prediction using at least one label of a plurality of synoptic annotations of the plurality of training images.