Kyungsang Kim
Kyungsang Kim
Assistant Professor at Harvard Medical School and Mass General Hospital
Verified email at - Homepage
Cited by
Cited by
Personalized iPSC-Derived Dopamine Progenitor Cells for Parkinson’s Disease
JS Schweitzer, B Song, TM Herrington, TY Park, N Lee, S Ko, J Jeon, ...
New England Journal of Medicine, 1926-1932, 2020
Iterative PET image reconstruction using convolutional neural network representation
K Gong, J Guan, K Kim, X Zhang, J Yang, Y Seo, G El Fakhri, J Qi, Q Li
IEEE transactions on medical imaging 38 (3), 675-685, 2018
Iterative low-dose CT reconstruction with priors trained by artificial neural network
D Wu, K Kim, G El Fakhri, Q Li
IEEE transactions on medical imaging 36 (12), 2479-2486, 2017
PET image denoising using unsupervised deep learning
J Cui, K Gong, N Guo, C Wu, X Meng, K Kim, K Zheng, Z Wu, L Fu, B Xu, ...
European journal of nuclear medicine and molecular imaging 46, 2780-2789, 2019
Penalized PET reconstruction using deep learning prior and local linear fitting
K Kim, D Wu, K Gong, J Dutta, JH Kim, YD Son, HK Kim, G El Fakhri, Q Li
IEEE transactions on medical imaging 37 (6), 1478-1487, 2018
Real-time visualization of 3-D dynamic microscopic objects using optical diffraction tomography
K Kim, KS Kim, HJ Park, JC Ye, YK Park
Optics express 21 (26), 32269-32278, 2013
Sparse-view spectral CT reconstruction using spectral patch-based low-rank penalty
K Kim, JC Ye, W Worstell, J Ouyang, Y Rakvongthai, G El Fakhri, Q Li
IEEE transactions on medical imaging 34 (3), 748-760, 2014
Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images
K Gong, J Yang, K Kim, G El Fakhri, Y Seo, Q Li
Physics in Medicine & Biology 63 (12), 125011, 2018
Motion adaptive patch-based low-rank approach for compressed sensing cardiac cine MRI
H Yoon, KS Kim, D Kim, Y Bresler, JC Ye
IEEE transactions on medical imaging 33 (11), 2069-2085, 2014
Computationally efficient deep neural network for computed tomography image reconstruction
D Wu, K Kim, Q Li
Medical physics 46 (11), 4763-4776, 2019
A cascaded convolutional neural network for X-ray low-dose CT image denoising
D Wu, K Kim, GE Fakhri, Q Li
arXiv preprint arXiv:1705.04267, 2017
Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-19
A Zhong, X Li, D Wu, H Ren, K Kim, Y Kim, V Buch, N Neumark, B Bizzo, ...
Medical Image Analysis 70, 101993, 2021
Consensus neural network for medical imaging denoising with only noisy training samples
D Wu, K Gong, K Kim, X Li, Q Li
International Conference on Medical Image Computing and Computer-Assisted …, 2019
Fully 3D iterative scatter-corrected OSEM for HRRT PET using a GPU
KS Kim, JC Ye
Physics in Medicine & Biology 56 (15), 4991, 2011
Low‐dose CT reconstruction using spatially encoded nonlocal penalty
K Kim, G El Fakhri, Q Li
Medical physics 44 (10), e376-e390, 2017
Artificial intelligence matches subjective severity assessment of pneumonia for prediction of patient outcome and need for mechanical ventilation: a cohort study
S Ebrahimian, F Homayounieh, MABC Rockenbach, P Putha, T Raj, ...
Scientific Reports 11 (1), 858, 2021
Metal artifact reduction in CT by identifying missing data hidden in metals
HS Park, JK Choi, KR Park, KS Kim, SH Lee, JC Ye, JK Seo
Journal of X-ray science and technology 21 (3), 357-372, 2013
Severity and consolidation quantification of COVID-19 from CT images using deep learning based on hybrid weak labels
D Wu, K Gong, CD Arru, F Homayounieh, B Bizzo, V Buch, H Ren, K Kim, ...
IEEE Journal of Biomedical and Health Informatics 24 (12), 3529-3538, 2020
MAPEM-Net: an unrolled neural network for Fully 3D PET image reconstruction
K Gong, D Wu, K Kim, J Yang, T Sun, G El Fakhri, Y Seo, Q Li
15th International meeting on fully three-dimensional image reconstruction …, 2019
Low‐dose CT reconstruction with Noise2Noise network and testing‐time fine‐tuning
D Wu, K Kim, Q Li
Medical Physics 48 (12), 7657-7672, 2021
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