	US 11,983,912 B2
	Pathology predictions on unstained tissue
Martin Stumpe, Mountain View, CA (US); and Lily Peng, Mountain View, CA (US)
Assigned to VERILY LIFE SCIENCES LLC, South San Francisco, CA (US)
Appl. No. 16/958,548
Filed by VERILY LIFE SCIENCES LLC, South San Francisco, CA (US)
PCT Filed Sep. 7, 2018, PCT No. PCT/US2018/049989 § 371(c)(1), (2) Date Jun. 26, 2020, PCT Pub. No. WO2019/160580, PCT Pub. Date Aug. 22, 2019.
Claims priority of provisional application 62/631,259, filed on Feb. 15, 2018.
Prior Publication US 2021/0064845 A1, Mar. 4, 2021
Int. Cl. G06V 10/25 (2022.01); G01N 1/30 (2006.01); G06T 7/00 (2017.01); G06V 20/69 (2022.01)

CPC G06V 10/25 (2022.01) [G01N 1/30 (2013.01); G06T 7/0012 (2013.01); G06V 20/695 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30068 (2013.01)]

20 Claims

1. A method of training a pattern recognizer to identify regions of interest in a tissue sample, comprising the steps of:

obtaining magnified digital images of the tissue sample, one of which represents the tissue sample after having been stained with a staining agent (“stained image”) and one of which represents the tissue sample in an unstained state (“unstained image”),

annotating the stained image so as to form a mask surrounding a region of interest (“ROI”) in the stained image;

transferring the mask from the stained image to the unstained image; and

training the pattern recognizer to identify ROIs in unstained images of tissue samples using the unstained image having the transferred mask as a training example.