Jong Chul Ye

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Hyungjin ChungKAISTVerified email at kaist.ac.kr
Kyong Hwan JinAssociate Professor of EE, Korea UniversityVerified email at korea.ac.kr
Yoseob HanAssistant Professor at Soongsil University, School of Electronic EngineeringVerified email at ssu.ac.kr
Jaeduck JangSAITVerified email at kaist.ac.kr
Sungho TakKorea Basic Science InstituteVerified email at kbsi.re.kr
Dongwook LeeSAIT, Samsung ElectronicsVerified email at samsung.com
Sangjoon ParkDepartment of Radiation Oncology, Yonsei University College of MedicineVerified email at yuhs.ac
Jaejun YooAssistant Professor, Laboratory of Advanced Imaging Technology (LAIT), UNISTVerified email at unist.ac.kr
Kyungsang KimAssistant Professor at Harvard Medical School and Mass General HospitalVerified email at mgh.harvard.edu
Yujin OhMassachusetts General Hospital & Harvard Medical SchoolVerified email at mgh.harvard.edu
Jaeyoung HuhSiemens Healthineers, Princeton, NJVerified email at siemens-healthineers.com
Eunhee KangSamsung Advanced Institute of Technology (SAIT)Verified email at samsung.com
Shujaat KhanSenior AI Scientist at Digital Technology & Innovation, Siemens Medical Solutions USA, Inc.Verified email at siemens-healthineers.com
Okkyun LeeDaegu Gyeongbuk Institute of Science and Technology (DGIST)Verified email at dgist.ac.kr
Kevin WebbProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
Rick MillaneUniversity of Canterbury, New ZealandVerified email at canterbury.ac.nz
Boah KimNational Institutes of HealthVerified email at nih.gov
Yoram BreslerFounder Professor of Engineering, Depts. of Electrical & Computer Engineering and BioengineeringVerified email at illinois.edu
Jong Min KimDept. of Mathematics and Computer Science, Korea Science Academy of KAISTVerified email at kaist.ac.kr
Eunju ChaAssistant Professor, Dept. of Electrical Engineering, Sookmyung Women's UniversityVerified email at sookmyung.ac.kr

Jong Chul Ye

Professor, Chung Moon Soul Mirae Endowed Chair, KAIST

Verified email at kaist.ac.kr - Homepage

machine learning computational imaging medical imaging signal processing compressed sensing


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Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017	2148	2017
NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy JC Ye, S Tak, KE Jang, J Jung, J Jang Neuroimage 44 (2), 428-447, 2009	1193	2009
A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction E Kang, J Min, JC Ye Medical physics 44 (10), e360-e375, 2017	946	2017
Deep learning COVID-19 features on CXR using limited training data sets Y Oh, S Park, JC Ye IEEE transactions on medical imaging 39 (8), 2688-2700, 2020	944	2020
k‐t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI H Jung, K Sung, KS Nayak, EY Kim, JC Ye Magnetic Resonance in Medicine: An Official Journal of the International …, 2009	870	2009
Diffusionclip: Text-guided diffusion models for robust image manipulation G Kim, T Kwon, JC Ye Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022	690	2022
Geometric gan JH Lim, JC Ye arXiv preprint arXiv:1705.02894, 2017	664	2017
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	649	2018
Diffusion posterior sampling for general noisy inverse problems H Chung, J Kim, MT Mccann, ML Klasky, JC Ye arXiv preprint arXiv:2209.14687, 2022	557	2022
Image reconstruction is a new frontier of machine learning G Wang, JC Ye, K Mueller, JA Fessler IEEE transactions on medical imaging 37 (6), 1289-1296, 2018	514	2018
Statistical analysis of fNIRS data: a comprehensive review S Tak, JC Ye Neuroimage 85, 72-91, 2014	491	2014
Deep learning for tomographic image reconstruction G Wang, JC Ye, B De Man Nature machine intelligence 2 (12), 737-748, 2020	475	2020
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	396	2018
Deep residual learning for accelerated MRI using magnitude and phase networks D Lee, J Yoo, S Tak, JC Ye IEEE Transactions on Biomedical Engineering 65 (9), 1985-1995, 2018	376	2018
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	354	2018
-Space Deep Learning for Accelerated MRI Y Han, L Sunwoo, JC Ye IEEE transactions on medical imaging 39 (2), 377-386, 2019	349	2019
Deep convolutional framelet denosing for low-dose ct via wavelet residual network E Kang, W Chang, J Yoo, JC Ye IEEE transactions on medical imaging 37 (6), 1358-1369, 2018	342	2018
Improved k–t BLAST and k–t SENSE using FOCUSS H Jung, JC Ye, EY Kim Physics in Medicine & Biology 52 (11), 3201, 2007	340	2007
Improving diffusion models for inverse problems using manifold constraints H Chung, B Sim, D Ryu, JC Ye Advances in Neural Information Processing Systems 35, 25683-25696, 2022	338	2022
Score-based diffusion models for accelerated MRI H Chung, JC Ye arXiv preprint arXiv:2110.05243, 2021	336	2021

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