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11.发明授权公开(公告)号：US10991132B2
公开(公告)日：2021-04-27
申请号：US16365498
申请日：2019-03-26
Inventor： JongChul Ye , Yoseob Han
Abstract: A method for processing a sparse-view computed tomography (CT) image using a neural network and an apparatus therefor are provided. The method includes receiving a sparse-view CT data and reconstructing an image for the sparse-view CT data using a neural network of a learning model satisfying a predetermined frame condition.
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12.发明申请公开(公告)号：US20200072933A1
公开(公告)日：2020-03-05
申请号：US16549500
申请日：2019-08-23
Inventor： JongChul Ye , Ju Young Lee
IPC: G01R33/565 , G01R33/56 , G01R33/561 , G06N3/08
Abstract: Disclosed herein are a method and an apparatus for removing ghost artifacts of an echo planner image using a neural network. An image processing method according to an embodiment of the inventive concept includes receiving Fourier space data of an echo planar image, and restoring the echo planar image in which ghost artifacts are removed using a neural network. The receiving of the Fourier space data may include dividing the Fourier space data into the odd-numbered Fourier space data and even-numbered Fourier space data, and the restoring of the echo planar image may include obtaining the odd-numbered Fourier space data and even-numbered Fourier space data with the Fourier space interpolated using the neural network and restoring the echo planar image in which the ghost artifacts are removed based on the odd-numbered Fourier space data and even-numbered Fourier space data with the Fourier space interpolated.
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公开(公告)号：US20220036564A1
公开(公告)日：2022-02-03
申请号：US17352229
申请日：2021-06-18
Inventor： JongChul Ye , Sangjoon Park , Yujin Oh , Gwanghyun Kim
Abstract: Disclosed are a method of classifying lesions of chest x-ray radiographs based on data normalization and local patches and an apparatus thereof. The method includes converting an input chest x-ray radiograph into a normalized image, segmenting the converted normalized image into an organ area by using a first neural network based on a pre-learned segmentation model, generating local patches for the segmented organ area, and classifying a lesion in the input chest x-ray radiograph by using a second neural network based on a pre-learned classification model for the generated local patches.
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公开(公告)号：US20220027741A1
公开(公告)日：2022-01-27
申请号：US17332696
申请日：2021-05-27
Inventor： JongChul Ye , Byeongsu Sim , Gyutaek Oh
Abstract: Disclosed are an unsupervised learning method and an apparatus therefor applicable to general inverse problems. An unsupervised learning method applicable to inverse problems includes receiving a training data set and training an unsupervised learning-based neural network generated based on an optimal transport theory and a penalized least square (PLS) approach using the training data set, wherein the receiving of the training data set includes receiving the training data set including unmatched data.
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15.发明申请公开(公告)号：US20220020155A1
公开(公告)日：2022-01-20
申请号：US17376588
申请日：2021-07-15
Inventor： JongChul Ye , Boah Kim
Abstract: Disclosed is an image segmentation method including receiving an image to be segmented and segmenting the received image by using a neural network learned through a Mumford-Shah function-based loss function.
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Patent Agency Ranking
公开(公告)号：US10853977B2
公开(公告)日：2020-12-01
申请号：US16109963
申请日：2018-08-23
Inventor： JongChul Ye , YoSeob Han , Eunju Cha
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.
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17.发明申请公开(公告)号：US20190355093A1
公开(公告)日：2019-11-21
申请号：US16414372
申请日：2019-05-16
Inventor： JongChul Ye , Yeohun Yoon , Shujaat Khan , Jaeyoung Huh
Abstract: An image processing apparatus according to an embodiment removes the noise included in the three-dimensional input image, determines the lost information in a process of obtaining the three-dimensional input image, or enhances the resolution of the three-dimensional input image, by using the neural network learned in advance. The image processing apparatus slices the three-dimensional input image along a depth, converts a three-dimensional input image into a two-dimensional input image, and inputs the converted two-dimensional input image into a neural network. The image processing apparatus generates a three-dimensional output image of which the quality of the three-dimensional input image is enhanced, based on the output of the neural network.
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公开(公告)号：US12175621B2
公开(公告)日：2024-12-24
申请号：US17365598
申请日：2021-07-01
Inventor： JongChul Ye , Boah Kim
Abstract: Disclosed are an unsupervised learning-based image registration method using a neural network with cycle consistency and an apparatus therefor. An image registration method includes receiving a first image and a second image for image registration, outputting a deformation field for the first image and the second image using an unsupervised learning-based neural network with cycle consistency for the deformation field, and generating a registration image for the first image and the second image based on a spatial deformation function using the output deformation field. The outputting of the deformation field includes outputting the deformation field for the first image for registering the first image to the second image may be output, when the first image is a moving image and the second image is a fixed image, and the generating of the registration image includes generating the registration image by applying the deformation field for the first image to the first image using the spatial deformation function.
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19.发明授权公开(公告)号：US12159410B2
公开(公告)日：2024-12-03
申请号：US17376588
申请日：2021-07-15
Inventor： JongChul Ye , Boah Kim
Abstract: Disclosed is an image segmentation method including receiving an image to be segmented and segmenting the received image by using a neural network learned through a Mumford-Shah function-based loss function.
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公开(公告)号：US11748851B2
公开(公告)日：2023-09-05
申请号：US16706224
申请日：2019-12-06
Inventor： JongChul Ye , Dongwook Lee
CPC classification number: G06T5/001 , G06N3/045 , G06N3/08 , G06N20/20 , G06T5/50 , G06T2207/20081 , G06T2207/20084 , G06T2207/20212
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.
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