公开(公告)号：US20230154069A1

公开(公告)日：2023-05-18

申请号：US18054794

申请日：2022-11-11

Applicant: Korea Advanced Institute of Science and Technology

Inventor： JongChul YE ,  Hyungjin CHUNG

IPC: G06T11/00 ,  G06T5/00

CPC classification number: G06T11/006 ,  G06T5/002 ,  G06T2207/20084 ,  G06T2207/20081

Abstract: A magnetic resonance imaging (MRI) recovery method using a score-based diffusion model and an apparatus thereof are provided. The MRI recovery method using the score-based diffusion model, which is performed by a computer, is implemented, including training a continuous time-dependent score function with denoising score matching and sampling data from a conditional distribution given the measurements, leveraging the learned score function, and recovering an image.

公开(公告)号：US20240104392A1

公开(公告)日：2024-03-28

申请号：US18351945

申请日：2023-07-13

Applicant: Korea Advanced Institute of Science and Technology

Inventor： JongChul YE ,  Sangjoon PARK

IPC: G06N3/098 ,  G06V10/774 ,  G06V10/94

CPC classification number: G06N3/098 ,  G06V10/7747 ,  G06V10/95

Abstract: Disclosed are a distributed learning-based multi-task vision transformer through random patch permutation and a transformation method using the same. The transformation method using the distributed learning-based multi-task vision transformer through random patch permutation may include preparing, using a task non-specific patch embedder, a patch embedding for each client and passing the patch embedding through a permutation module and then transmitting the patch embedding to a server; and storing ; by the server, the received patch embedding and using the patch embedding to update body and tail parts of a vision transformer model.

公开(公告)号：US20210030400A1

公开(公告)日：2021-02-04

申请号：US16721015

申请日：2019-12-19

Applicant: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor： JongChul YE ,  Shujaat KHAN ,  Jaeyoung HUH

IPC: A61B8/08 ,  G06T7/00

Abstract: An apparatus and method for processing an ultrasound image in various sensor conditions are provided. The method includes receiving a data cube via sensors, transforming the received data cube into focus data through beam focusing, and outputting inphase data and quadrature phase data for the focus data using a neural network corresponding to signal adder and Hilbert transform functions. The method further includes detecting an envelope of the inphase data and the quadrature phase data and reconstructing an ultrasound image for the data cube using log compression.

公开(公告)号：US20200311874A1

公开(公告)日：2020-10-01

申请号：US16706224

申请日：2019-12-06

Applicant: Korea Advanced Institute of Science and Technology

Inventor： JongChul YE ,  Dongwook LEE

IPC: G06T5/00 ,  G06T5/50 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20

Abstract: Disclosed are a method and apparatus for replacing missing image data. The method of replacing missing image data includes receiving input image data for at least two or more domains among preset multiple domains, and restoring missing image data of a preset target domain by using a neural network that uses the two or more input image data as inputs. The neural network may combine fake image data of a first target domain generated by inputting real image data of at least two or more domains of the multiple domains and the real image data, and be trained by using a multi-cycle consistency loss in which an image restored by inputting the combined image data is similar with the real image data.

公开(公告)号：US20190066346A1

公开(公告)日：2019-02-28

申请号：US16109963

申请日：2018-08-23

Applicant: Korea Advanced Institute Of Science and Technology

Inventor： JongChul YE ,  YoSeob HAN ,  Eunju CHA

IPC: G06T11/00

Abstract: A method and apparatus for reconstructing an image using an extended neural network is provided. The method includes receiving an input image and reconstructing an output image from the input image using a neural network meeting a predetermined frame constraint. The reconstructing includes transforming the input image into signals corresponding to different frequencies, adjusting coefficients of the transformed signals using a nonlinear function, reconstructing the adjusted coefficients, and inversely transforming all coefficients determined using the reconstructed coefficients into the output image.