재정 지원 요구사항을 통해 공개된 자료 - Yoseob Han자세히 알아보기
제공된 곳이 없음: 1
Cone-angle artifact removal using differentiated backprojection domain deep learning
J Kim, Y Han, JC Ye
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 642-645, 2020
재정 지원 요구사항 정책: US National Institutes of Health
제공된 곳이 있음: 7
Framing U-Net via deep convolutional framelets: Application to sparse-view CT
Y Han, JC Ye
IEEE transactions on medical imaging 37 (6), 1418-1429, 2018
재정 지원 요구사항 정책: US National Institutes of Health
Deep convolutional framelets: A general deep learning framework for inverse problems
JC Ye, Y Han, E Cha
SIAM Journal on Imaging Sciences 11 (2), 991-1048, 2018
재정 지원 요구사항 정책: US National Institutes of Health
Deep learning with domain adaptation for accelerated projection‐reconstruction MR
Y Han, J Yoo, HH Kim, HJ Shin, K Sung, JC Ye
Magnetic resonance in medicine 80 (3), 1189-1205, 2018
재정 지원 요구사항 정책: US National Institutes of Health
One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection
Y Han, JC Ye
Medical physics 46 (12), e855-e872, 2019
재정 지원 요구사항 정책: US National Institutes of Health
Differentiated backprojection domain deep learning for conebeam artifact removal
Y Han, J Kim, JC Ye
IEEE Transactions on Medical Imaging 39 (11), 3571-3582, 2020
재정 지원 요구사항 정책: US National Institutes of Health
Uncertainties in Density and Simulation Parameters for Radiographic Reconstructions Using Machine Learning
ML Klasky, BT Nadiga, JLS Disterhaupt, T Wilcox, LD Hovey, T Mockler, ...
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2020
재정 지원 요구사항 정책: US Department of Energy
Hydrodynamic and Radiographic Toolbox (HART)
ML Klasky, BT Nadiga, JLS Disterhaupt, E Guardincerri, JL Carroll, ...
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2020
재정 지원 요구사항 정책: US Department of Energy
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