US 11,741,604 B2
Systems and methods for processing electronic images to infer biomarkers
Supriya Kapur, New York, NY (US); Ran Godrich, New York, NY (US); Christopher Kanan, Pittsford, 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 Jul. 5, 2022, as Appl. No. 17/810,815.
Application 17/810,815 is a continuation of application No. 17/016,048, filed on Sep. 9, 2020.
Claims priority of provisional application 62/897,734, filed on Sep. 9, 2019.
Prior Publication US 2022/0335607 A1, Oct. 20, 2022
Int. Cl. G06T 7/00 (2017.01); G06T 7/11 (2017.01); G16H 10/40 (2018.01); G16H 50/20 (2018.01); G16H 30/40 (2018.01); G06V 20/69 (2022.01); G06F 18/214 (2023.01)
CPC G06T 7/0012 (2013.01) [G06F 18/214 (2023.01); G06T 7/11 (2017.01); G06V 20/695 (2022.01); G06V 20/698 (2022.01); G16H 10/40 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01); G06V 2201/03 (2022.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method for analyzing a plurality of digital images corresponding to a pathology specimen, comprising:
receiving the plurality of digital images of the pathology specimen;
determining, by a machine learning system, a human epidermal growth factor receptor 2 (HER2) biomarker expression level prediction for the plurality of digital images, the machine learning system having been trained by processing a plurality of training images wherein determining the HER2 biomarker expression level prediction includes:
breaking each of the plurality of digital images into a plurality of tiles;
determining, by machine learning, a HER2 score corresponding to a prediction for each tile to determine a plurality of tile predictions, each HER2 score being based on immunohistochemistry (IHC) on a scale of 0, 1+, 1+ to 2+, 2+, and/or 3+; and
aggregating the plurality of tile predictions into at least one part level HER2 prediction, the HER2 biomarker expression level prediction being based on the at least one part level HER2 prediction; and
outputting, based on the HER2 biomarker expression level prediction, an HER2 score.