公开(公告)号：US20240212146A1

公开(公告)日：2024-06-27

申请号：US18506741

申请日：2023-11-10

Applicant: Lunit Inc.

Inventor： Jeongun RYU ,  Jaewoong SHIN ,  Aaron VALERO PUCHE ,  Seonwook PARK ,  Biagio BRATTOLI ,  Sêrgio PEREIRA ,  Donggeun YOO ,  Jinhee LEE

IPC: G06T7/00 ,  G06N20/00 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06N20/00 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10056 ,  G06T2207/30024

Abstract: A computing apparatus includes at least one memory, and at least one processor, wherein the processor is configured to acquire a pathological slide image showing at least one tissue, generate feature information related to at least one area of the pathological slide image, and detect, from the pathological slide image, at least one cell included in the at least one tissue by using the pathological slide image and the feature information.

公开(公告)号：US20250069420A1

公开(公告)日：2025-02-27

申请号：US18946457

申请日：2024-11-13

Applicant: Lunit Inc.

Inventor： Biagio BRATTOLI ,  Chan-Young Ock ,  Wonkyung Jung ,  Soo Ick Cho ,  Kyunghyun Paeng ,  Dong Geun Yoo

IPC: G06V20/69 ,  G06V10/22 ,  G06V10/98

Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.

公开(公告)号：US20240046670A1

公开(公告)日：2024-02-08

申请号：US18491314

申请日：2023-10-20

Applicant: Lunit Inc.

Inventor： Biagio BRATTOLI ,  Chan-Young OCK ,  Wonkyung JUNG ,  Soo lck CHO ,  Kyunghyun PAENG ,  Dong Geun YOO

IPC: G06V20/69 ,  G06V10/22 ,  G06V10/98

CPC classification number: G06V20/695 ,  G06V10/235 ,  G06V10/993

Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.