Hyungjin Chung
Hyungjin Chung
KAIST bio&brain engineering
Verified email at - Homepage
Cited by
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Unpaired deep learning for accelerated MRI using optimal transport driven CycleGAN
G Oh, B Sim, HJ Chung, L Sunwoo, JC Ye
IEEE Transactions on Computational Imaging 6, 1285-1296, 2020
Score-based diffusion models for accelerated MRI
H Chung, JC Ye
Medical Image Analysis 80 (102479), 2022
Improving diffusion models for inverse problems using manifold constraints
H Chung, B Sim, D Ryu, JC Ye
arXiv preprint arXiv:2206.00941, 2022
Unsupervised deep learning methods for biological image reconstruction and enhancement: an overview from a signal processing perspective
M Akçakaya, B Yaman, H Chung, JC Ye
IEEE Signal Processing Magazine 39 (2), 28-44, 2022
Deep learning STEM-EDX tomography of nanocrystals
Y Han, J Jang, E Cha, J Lee, H Chung, M Jeong, TG Kim, BG Chae, ...
Nature Machine Intelligence 3 (3), 267-274, 2021
Unpaired training of deep learning tMRA for flexible spatio-temporal resolution
E Cha, H Chung, EY Kim, JC Ye
IEEE Transactions on Medical Imaging 40 (1), 166-179, 2020
Diffusion posterior sampling for general noisy inverse problems
H Chung, J Kim, MT Mccann, ML Klasky, JC Ye
arXiv preprint arXiv:2209.14687, 2022
Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction
H Chung, B Sim, JC Ye
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data
H Chung, E Cha, L Sunwoo, JC Ye
Medical Image Analysis 71, 102047, 2021
Missing cone artifact removal in ODT using unsupervised deep learning in the projection domain
H Chung, J Huh, G Kim, YK Park, JC Ye
IEEE Transactions on Computational Imaging 7, 747-758, 2021
Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison
JY Nam, HJ Chung, KS Choi, H Lee, TJ Kim, H Soh, EA Kang, SJ Cho, ...
Gastrointestinal Endoscopy 95 (2), 258-268. e10, 2022
Deep learning fast MRI using channel attention in magnitude domain
J Lee, H Kim, HJ Chung, JC Ye
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 917-920, 2020
MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion
H Chung, ES Lee, JC Ye
IEEE Transactions on Medical Imaging, 2022
Progressive deblurring of diffusion models for coarse-to-fine image synthesis
S Lee, H Chung, J Kim, JC Ye
arXiv preprint arXiv:2207.11192, 2022
Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning
H Chung, J Kim, JH Yoon, JM Lee, JC Ye
arXiv preprint arXiv:2105.00240, 2021
Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models
H Chung, D Ryu, MT McCann, ML Klasky, JC Ye
arXiv preprint arXiv:2211.10655, 2022
Parallel Diffusion Models of Operator and Image for Blind Inverse Problems
H Chung, J Kim, S Kim, JC Ye
arXiv preprint arXiv:2211.10656, 2022
Reusability report: Feature disentanglement in generating a three-dimensional structure from a two-dimensional slice with sliceGAN
H Chung, JC Ye
Nature Machine Intelligence 3 (10), 861-863, 2021
Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning
E Cha, H Chung, J Jang, J Lee, E Lee, JC Ye
ACS nano 16 (7), 10314-10326, 2022
Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models
S Lee, H Chung, M Park, J Park, WS Ryu, JC Ye
arXiv preprint arXiv:2303.08440, 2023
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