公开(公告)号：US20220262513A1

公开(公告)日：2022-08-18

申请号：US17550034

申请日：2021-12-14

Applicant: LUNIT INC.

Inventor： Donggeun YOO ,  Jaehong AUM ,  Minuk MA ,  Jeong Un RYU

IPC: G16H50/20 ,  G06N20/00 ,  G16H30/20

Abstract: A method, performed by at least one processor, for training a machine learning model for detecting an abnormal region in a pathological slide image is disclosed. The method including receiving one or more first pathological slide images, determining, from the received one or more first pathological slide images, a normal region based on an abnormality condition indicative of a condition of an abnormal region, generating a first set of training data including the determined normal region, generating the abnormal region by performing image processing corresponding to the abnormality condition with respect to at least partial region in the received one or more first pathological slide images, and generating a second set of training data including the generated abnormal region.

公开(公告)号：US20220261988A1

公开(公告)日：2022-08-18

申请号：US17551506

申请日：2021-12-15

Applicant: LUNIT INC.

Inventor： Donggeun YOO ,  Jaehong AUM ,  Minuk MA ,  Jeong Un RYU

IPC: G06T7/00 ,  G16H10/40 ,  G16H70/60 ,  G16H30/20 ,  G16H30/40

Abstract: A method for detecting a region of interest (ROI) in a pathological slide image is provided. The method may include receiving one or more pathological slide images and detecting an ROI in the received one or more pathological slide images. In addition, an information processing system is provided. The information processing system includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions to receive one or more pathological slide images and detect an ROI in the received one or more pathological slide images.