US 11,710,552 B2
Method and system for refining label information
Chunseong Park, Seoul (KR)
Assigned to LUNIT INC., Seoul (KR)
Filed by LUNIT INC., Seoul (KR)
Filed on Nov. 20, 2020, as Appl. No. 16/953,693.
Claims priority of application No. 10-2020-0061582 (KR), filed on May 22, 2020.
Prior Publication US 2021/0366594 A1, Nov. 25, 2021
Int. Cl. G16H 30/40 (2018.01); G06T 7/11 (2017.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01)
CPC G16H 30/40 (2018.01) [G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for refining label information, performed by at least one computing device, the method comprising:
acquiring a pathology slide image including a plurality of patches;
inferring a plurality of label information items for the plurality of patches included in the acquired pathology slide image using a machine learning model;
applying the inferred plurality of label information items to the pathology slide image;
calculating at least one of a confidence score or an entropy value for each of the plurality of patches;
selecting at least one first patch to be refined from among the plurality of patches based on a comparison of at least one of the calculated confidence score or the entropy value and a predetermined value; and
providing the pathology slide image applied with the inferred plurality of label information items to an annotator terminal,
wherein the plurality of label information items for the plurality of patches includes a plurality of classes associated with the plurality of patches, and
the calculating at least one of the confidence score or the entropy value for each of the plurality of patches includes assigning a weight to the entropy value for a target class among the plurality of classes associated with the plurality of patches.