公开(公告)号：US20220172370A1

公开(公告)日：2022-06-02

申请号：US17533858

申请日：2021-11-23

Applicant: VUNO Inc. ,  SEOUL NATIONAL UNIVERSITY HOSPITAL

Inventor： Dong Soo LEE ,  Hyunwoo OH ,  Sejin PARK ,  Jinkyeong SUNG ,  Eunpyeong HONG ,  Weon Jin KIM ,  Ki Woong KIM ,  Jong Bin BAE ,  Subin LEE ,  Jun Sung KIM

IPC: G06T7/11

Abstract: According to an embodiment of the present disclosure, a method of detecting a white matter lesion based on a medical image performed by a computing device is disclosed. The method may include: receiving a medical image including at least one brain region; and estimating a first white matter lesion and a second white matter lesion based on the medical image using a pre-trained neural network model.

公开(公告)号：US20220180512A1

公开(公告)日：2022-06-09

申请号：US17539827

申请日：2021-12-01

Applicant: VUNO Inc.

Inventor： Hyunwoo OH ,  Sejin PARK ,  Jinkyeong SUNG ,  Weon Jin KIM ,  Eunpyeong HONG ,  Dong Soo LEE

IPC: G06T7/00 ,  G06T7/30 ,  G06T7/11 ,  A61B5/00 ,  G06N3/04 ,  G16H30/40 ,  G16H50/20

Abstract: Disclosed is a method for predicting disease based on a medical image performed by a computing device. The method includes: generating a feature vector related to predictive values of brain disease for each of 2D medical images included in a 3D medical image, using a pre-trained first model; estimating importance indicating prediction accuracy for each of the 2D medical images based on the feature vector, using a pre-trained second model; and selecting at least one model input image suitable for prediction of the brain disease from among the 2D medical images based on the importance.

公开(公告)号：US20220130065A1

公开(公告)日：2022-04-28

申请号：US17509590

申请日：2021-10-25

Applicant: VUNO Inc.

Inventor： Eunpyeong HONG ,  Wonmo JUNG ,  Sejin PARK ,  Hyunwoo OH ,  Dong Soo LEE ,  Weon Jin KIM ,  Jinkyeong SUNG

IPC: G06T7/62 ,  G06T7/00 ,  G06T17/20

Abstract: Disclosed is a method for analyzing a thickness of a cortical region, performed by a computing device. The method may include: extracting a plurality of interfaces included in a cortical region based on a mask generated from a medical image including at least one brain region; and estimating a thickness of the cortical region based on the plurality of interfaces.