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.

公开(公告)号：US20210295151A1

公开(公告)日：2021-09-23

申请号：US17077114

申请日：2020-10-22

Applicant: Lunit Inc.

Inventor： Donggeun YOO ,  Jeong Hoon LEE ,  Jae Hwan LEE

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G06K9/46

Abstract: There is provided a method and apparatus that collects feature points of data and performs machine learning. A machine learning method comprises receiving first feature data obtained by applying a basic model to first analysis target data, receiving second feature data obtained by applying the basic model to second analysis target data, and obtaining a final machine learning model through performing machine learning on a correlation between the first feature data and first analysis result data and a correlation between the second feature data and second analysis result data.

公开(公告)号：US20210012160A1

公开(公告)日：2021-01-14

申请号：US17035401

申请日：2020-09-28

Applicant: Lunit Inc.

Inventor： Jongchan PARK ,  Donggeun YOO

IPC: G06K9/62 ,  G16H30/20 ,  G06T7/70 ,  G06T7/00

Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.