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2020 – today
- 2021
[j56]Jawook Gu, Jong Chul Ye
:
AdaIN-Based Tunable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising. IEEE Trans. Computational Imaging 7: 73-85 (2021)- [j55]Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye:
Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution. IEEE Trans. Medical Imaging 40(1): 166-179 (2021) - [j54]DongHun Ryu, Dongmin Ryu, YoonSeok Baek, Hyungjoo Cho, Geon Kim, Young Seo Kim, Yongki Lee, Yoosik Kim, Jong Chul Ye, Hyunseok Min, YongKeun Park:
DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning. IEEE Trans. Medical Imaging 40(5): 1508-1518 (2021) - [c83]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Switchable Deep Beamformer For Ultrasound Imaging Using Adain. ISBI 2021: 677-680 - [c82]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Unsupervised Deep Learning For Accelerated High Quality Echocardiography. ISBI 2021: 1738-1741 - [i83]Sangjoon Park, Gwanghyun Kim, Yujin Oh, Joon Beom Seo, Sang Min Lee, Jin Hwan Kim, Sungjun Moon, Jae-Kwang Lim, Jong Chul Ye:
Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus. CoRR abs/2103.07055 (2021) - [i82]Gwanghyun Kim, Sangjoon Park, Yujin Oh, Joon Beom Seo, Sang Min Lee, Jin Hwan Kim, Sungjun Moon, Jae-Kwang Lim, Jong Chul Ye:
Severity Quantification and Lesion Localization of COVID-19 on CXR using Vision Transformer. CoRR abs/2103.07062 (2021) - [i81]Hyungjin Chung, Jaeyoung Huh, Geon Kim, YongKeun Park, Jong Chul Ye:
Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography. CoRR abs/2103.09022 (2021) - [i80]Gihyun Kwon, Jong Chul Ye:
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation. CoRR abs/2103.16146 (2021) - [i79]Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek:
PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing. CoRR abs/2104.02895 (2021) - [i78]Yujin Oh, Jong Chul Ye:
Unifying domain adaptation and self-supervised learning for CXR segmentation via AdaIN-based knowledge distillation. CoRR abs/2104.05892 (2021) - [i77]Sangjoon Park, Gwanghyun Kim, Yujin Oh, Joon Beom Seo, Sang Min Lee, Jin Hwan Kim, Sungjun Moon, Jae-Kwang Lim, Jong Chul Ye:
Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification. CoRR abs/2104.07235 (2021) - [i76]Taesung Kwon, Jong Chul Ye:
Cycle-free CycleGAN using Invertible Generator for Unsupervised Low-Dose CT Denoising. CoRR abs/2104.08538 (2021) - [i75]Hyoungjun Park, Myeongsu Na, Bumju Kim, Soohyun Park, Ki Hean Kim, Sunghoe Chang, Jong Chul Ye:
Axial-to-lateral super-resolution for 3D fluorescence microscopy using unsupervised deep learning. CoRR abs/2104.09435 (2021) - [i74]Hyungjin Chung, Jong Chul Ye:
Feature Disentanglement in generating three-dimensional structure from two-dimensional slice with sliceGAN. CoRR abs/2105.00194 (2021) - [i73]Hyungjin Chung, Jaehyun Kim, Jeong Hee Yoon, Jeong Min Lee, Jong Chul Ye:
Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning. CoRR abs/2105.00240 (2021) - [i72]Mehmet Akçakaya, Burhaneddin Yaman, Hyungjin Chung, Jong Chul Ye:
Unsupervised Deep Learning Methods for Biological Image Reconstruction. CoRR abs/2105.08040 (2021) - [i71]Byung-Hoon Kim, Jong Chul Ye, Jae-Jin Kim:
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention. CoRR abs/2105.13495 (2021) - [i70]Kwanyoung Kim, Jong Chul Ye:
Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images. CoRR abs/2106.07009 (2021) - 2020
- [j53]Mi-Sun Kang, Eunju Cha, Eunhee Kang, Jong Chul Ye, Nam-Gu Her, Jeong-Woo Oh, Do-Hyun Nam, Myoung-Hee Kim, Sejung Yang:
Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy images. Biomed. Signal Process. Control. 58: 101846 (2020) - [j52]Vishal Monga, Scott T. Acton, Abd-Krim Seghouane, Arrate Muñoz-Barrutia, Jong Chul Ye:
Editorial: Introduction to the Issue on Domain Enriched Learning for Medical Imaging. IEEE J. Sel. Top. Signal Process. 14(6): 1068-1071 (2020) - [j51]Eunju Cha, Gyutaek Oh, Jong Chul Ye:
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction. IEEE J. Sel. Top. Signal Process. 14(6): 1292-1305 (2020) - [j50]Saiprasad Ravishankar, Jong Chul Ye, Jeffrey A. Fessler:
Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning. Proc. IEEE 108(1): 86-109 (2020) - [j49]Byeongsu Sim, Gyutaek Oh, Jeongsol Kim, Chanyong Jung, Jong Chul Ye:
Optimal Transport Driven CycleGAN for Unsupervised Learning in Inverse Problems. SIAM J. Imaging Sci. 13(4): 2281-2306 (2020) - [j48]Mathews Jacob, Jong Chul Ye, Leslie Ying, Mariya Doneva:
Computational MRI: Compressive Sensing and Beyond [From the Guest Editors]. IEEE Signal Process. Mag. 37(1): 21-23 (2020) - [j47]Mathews Jacob, Merry P. Mani, Jong Chul Ye:
Structured Low-Rank Algorithms: Theory, Magnetic Resonance Applications, and Links to Machine Learning. IEEE Signal Process. Mag. 37(1): 54-68 (2020) - [j46]Sungjun Lim, Hyoungjun Park, Sang-Eun Lee, Sunghoe Chang, Byeongsu Sim, Jong Chul Ye:
CycleGAN With a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry. IEEE Trans. Computational Imaging 6: 1127-1138 (2020) - [j45]Gyutaek Oh, Byeongsu Sim, Hyungjin Chung, Leonard Sunwoo, Jong Chul Ye:
Unpaired Deep Learning for Accelerated MRI Using Optimal Transport Driven CycleGAN. IEEE Trans. Computational Imaging 6: 1285-1296 (2020) - [j44]Boah Kim, Jong Chul Ye:
Mumford-Shah Loss Functional for Image Segmentation With Deep Learning. IEEE Trans. Image Process. 29: 1856-1866 (2020) - [j43]Yoseob Han, Leonard Sunwoo, Jong Chul Ye:
k-Space Deep Learning for Accelerated MRI. IEEE Trans. Medical Imaging 39(2): 377-386 (2020) - [j42]Jae Jun Yoo, Sohail Sabir, Duchang Heo, Kee Hyun Kim, Abdul Wahab, Yoonseok Choi, Seul-I Lee, Eun Young Chae, Hak Hee Kim, Young Min Bae, Young-Wook Choi, Seungryong Cho, Jong Chul Ye:
Deep Learning Diffuse Optical Tomography. IEEE Trans. Medical Imaging 39(4): 877-887 (2020) - [j41]Yujin Oh, Sangjoon Park, Jong Chul Ye:
Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets. IEEE Trans. Medical Imaging 39(8): 2688-2700 (2020) - [j40]Yoseob Han, Junyoung Kim, Jong Chul Ye:
Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal. IEEE Trans. Medical Imaging 39(11): 3571-3582 (2020) - [c81]Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Jing Liu, Kwangjin Yoon, Taegyun Jeon, Kazutoshi Akita, Takeru Ooba, Norimichi Ukita, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Dongliang He, Wenhao Wu, Yukang Ding, Chao Li, Fu Li, Shilei Wen, Jianwei Li, Fuzhi Yang, Huan Yang, Jianlong Fu, Byung-Hoon Kim, JaeHyun Baek, Jong Chul Ye, Yuchen Fan, Thomas S. Huang, Junyeop Lee, Bokyeung Lee, Jungki Min, Gwantae Kim, Kanghyu Lee, Jaihyun Park, Mykola Mykhailych, Haoyu Zhong, Yukai Shi, Xiaojun Yang, Zhijing Yang, Liang Lin, Tongtong Zhao, Jinjia Peng, Huibing Wang, Zhi Jin, Jiahao Wu, Yifu Chen, Chenming Shang, Huanrong Zhang, Jeongki Min, Hrishikesh P. S, Densen Puthussery, C. V. Jiji:
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results. CVPR Workshops 2020: 2045-2057 - [c80]Andrey Ignatov, Radu Timofte, Zhilu Zhang, Ming Liu, Haolin Wang, Wangmeng Zuo, Jiawei Zhang, Ruimao Zhang, Zhanglin Peng, Sijie Ren, Linhui Dai, Xiaohong Liu, Chengqi Li, Jun Chen, Yuichi Ito, Bhavya Vasudeva, Puneesh Deora, Umapada Pal, Zhenyu Guo, Yu Zhu, Tian Liang, Chenghua Li, Cong Leng, Zhihong Pan, Baopu Li, Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek, Magauiya Zhussip, Yeskendir Koishekenov, Hwechul Cho Ye, Xin Liu, Xueying Hu, Jun Jiang, Jinwei Gu, Kai Li, Pengliang Tang, Bingxin Hou:
AIM 2020 Challenge on Learned Image Signal Processing Pipeline. ECCV Workshops (3) 2020: 152-170 - [c79]Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek:
PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing. ECCV Workshops (3) 2020: 202-212 - [c78]Byeongsu Sim, Gyutaek Oh, Jong Chul Ye:
Optimal Transport Structure of CycleGAN for Unsupervised Learning for Inverse Problems. ICASSP 2020: 8644-8647 - [c77]Sangjoon Park, Jong Chul Ye:
Unsupervised Cone-Beam Artifact Removal Using CycleGAN and Spectral Blending for Adaptive Radiotherapy. ISBI 2020: 638-641 - [c76]Junyoung Kim, Yoseob Han, Jong Chul Ye:
Cone-Angle Artifact Removal Using Differentiated Backprojection Domain Deep Learning. ISBI 2020: 642-645 - [c75]Joonhyung Lee, Hyunjong Kim, Hyungjin Chung, Jong Chul Ye:
Deep Learning Fast MRI Using Channel Attention in Magnitude Domain. ISBI 2020: 917-920 - [c74]Gyutaek Oh, Byeongsu Sim, Jong Chul Ye:
Unsupervised Learning for Compressed Sensing MRI Using Cyclegan. ISBI 2020: 1082-1085 - [e2]Farah Deeba, Patricia Johnson, Tobias Würfl, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12450, Springer 2020, ISBN 978-3-030-61597-0 [contents] - [i69]Byung-Hoon Kim, Jong Chul Ye:
Understanding Graph Isomorphism Network for Brain MR Functional Connectivity Analysis. CoRR abs/2001.03690 (2020) - [i68]Joonyoung Song, Jae-Heon Jeong, Dae-Soon Park, Hyun-Ho Kim, Doo-Chun Seo, Jong Chul Ye:
Unsupervised Denoising for Satellite Imagery using Wavelet Subband CycleGAN. CoRR abs/2002.09847 (2020) - [i67]Eunju Cha, Gyutaek Oh, Jong Chul Ye:
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction. CoRR abs/2003.07740 (2020) - [i66]Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye:
Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution. CoRR abs/2003.13096 (2020) - [i65]Yujin Oh, Sangjoon Park, Jong Chul Ye:
Deep Learning COVID-19 Features on CXR using Limited Training Data Sets. CoRR abs/2004.05758 (2020) - [i64]Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Jing Liu, Kwangjin Yoon, Taegyun Jeon, Kazutoshi Akita, Takeru Ooba, Norimichi Ukita, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Dongliang He, Wenhao Wu, Yukang Ding, Chao Li, Fu Li, Shilei Wen, Jianwei Li, Fuzhi Yang, Huan Yang, Jianlong Fu, Byung-Hoon Kim, JaeHyun Baek, Jong Chul Ye, Yuchen Fan, Thomas S. Huang, Junyeop Lee, Bokyeung Lee, Jungki Min, Gwantae Kim, Kanghyu Lee, Jaihyun Park, Mykola Mykhailych, Haoyu Zhong, Yukai Shi, Xiaojun Yang, Zhijing Yang, Liang Lin, Tongtong Zhao, Jinjia Peng, Huibing Wang, Zhi Jin, Jiahao Wu, Yifu Chen, Chenming Shang, Huanrong Zhang, Jeongki Min, Hrishikesh P. S, Densen Puthussery, C. V. Jiji:
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results. CoRR abs/2005.01056 (2020) - [i63]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal. CoRR abs/2006.14773 (2020) - [i62]Junghyun Lee, Jawook Gu, Jong Chul Ye:
Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN. CoRR abs/2007.03480 (2020) - [i61]Jaeyoung Huh, Shujaat Khan, Jong Chul Ye:
OT-driven Multi-Domain Unsupervised Ultrasound Image Artifact Removal using a Single CNN. CoRR abs/2007.05205 (2020) - [i60]Hyungjin Chung, Eunju Cha, Leonard Sunwoo, Jong Chul Ye:
Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data. CoRR abs/2008.01362 (2020) - [i59]Jawook Gu, Jong Chul Ye:
AdaIN-Switchable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising. CoRR abs/2008.05753 (2020) - [i58]Boah Kim, Dong Hwan Kim, Seong Ho Park, Jieun Kim, June-Goo Lee, Jong Chul Ye:
CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration. CoRR abs/2008.05772 (2020) - [i57]Gyutaek Oh, Byeongsu Sim, Hyungjin Chung, Leonard Sunwoo, Jong Chul Ye:
Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGAN. CoRR abs/2008.12967 (2020) - [i56]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Switchable Deep Beamformer. CoRR abs/2008.13646 (2020) - [i55]Andrey Ignatov, Radu Timofte, Zhilu Zhang, Ming Liu, Haolin Wang, Wangmeng Zuo, Jiawei Zhang, Ruimao Zhang, Zhanglin Peng, Sijie Ren, Linhui Dai, Xiaohong Liu, Chengqi Li, Jun Chen, Yuichi Ito, Bhavya Vasudeva, Puneesh Deora, Umapada Pal, Zhenyu Guo, Yu Zhu, Tian Liang, Chenghua Li, Cong Leng, Zhihong Pan, Baopu Li, Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek, Magauiya Zhussip, Yeskendir Koishekenov, Hwechul Cho, Xin Liu, Xueying Hu, Jun Jiang, Jinwei Gu, Kai Li, Pengliang Tang, Bingxin Hou:
AIM 2020 Challenge on Learned Image Signal Processing Pipeline. CoRR abs/2011.04994 (2020) - [i54]Gyutaek Oh, Jeong Eun Lee, Jong Chul Ye:
Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation. CoRR abs/2011.06337 (2020) - [i53]Eunju Cha, Chanseok Lee, Mooseok Jang, Jong Chul Ye:
DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval. CoRR abs/2011.10475 (2020) - [i52]Serin Yang, Eung-Yeop Kim, Jong Chul Ye:
Continuous Conversion of CT Kernel using Switchable CycleGAN with AdaIN. CoRR abs/2011.13150 (2020) - [i51]Gyutaek Oh, Hyokyoung Bae, Hyun-Seo Ahn, Sung-Hong Park, Jong Chul Ye:
CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN. CoRR abs/2012.03842 (2020)
2010 – 2019
- 2019
- [j39]Yeo Hun Yoon, Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning. IEEE Trans. Medical Imaging 38(2): 325-336 (2019) - [c73]Dongwook Lee, Junyoung Kim, Won-Jin Moon, Jong Chul Ye:
CollaGAN: Collaborative GAN for Missing Image Data Imputation. CVPR 2019: 2487-2496 - [c72]Jong Chul Ye, Woon Kyoung Sung:
Understanding Geometry of Encoder-Decoder CNNs. ICML 2019: 7064-7073 - [c71]Boah Kim, Jieun Kim, June-Goo Lee, Dong Hwan Kim, Seong Ho Park, Jong Chul Ye:
Unsupervised Deformable Image Registration Using Cycle-Consistent CNN. MICCAI (6) 2019: 166-174 - [c70]Sungjun Lim, Jong Chul Ye:
Blind Deconvolution Microscopy Using Cycle Consistent CNN with Explicit PSF Layer. MLMIR@MICCAI 2019: 173-180 - [c69]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Deep Learning-Based Universal Beamformer for Ultrasound Imaging. MICCAI (5) 2019: 619-627 - [e1]Florian Knoll, Andreas Maier, Daniel Rueckert, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11905, Springer 2019, ISBN 978-3-030-33842-8 [contents] - [i50]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Universal Deep Beamformer for Variable Rate Ultrasound Imaging. CoRR abs/1901.01706 (2019) - [i49]Jong Chul Ye, Woon Kyoung Sung:
Understanding Geometry of Encoder-Decoder CNNs. CoRR abs/1901.07647 (2019) - [i48]Dongwook Lee, Junyoung Kim, Won-Jin Moon, Jong Chul Ye:
CollaGAN : Collaborative GAN for Missing Image Data Imputation. CoRR abs/1901.09764 (2019) - [i47]Saiprasad Ravishankar, Jong Chul Ye, Jeffrey A. Fessler:
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning. CoRR abs/1904.02816 (2019) - [i46]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Deep Learning-based Universal Beamformer for Ultrasound Imaging. CoRR abs/1904.02843 (2019) - [i45]Boah Kim, Jong Chul Ye:
Multiphase Level-Set Loss for Semi-Supervised and Unsupervised Segmentation with Deep Learning. CoRR abs/1904.02872 (2019) - [i44]Sungjun Lim, Sang-Eun Lee, Sunghoe Chang, Jong Chul Ye:
Blind Deconvolution Microscopy Using Cycle Consistent CNN with Explicit PSF Layer. CoRR abs/1904.02910 (2019) - [i43]Dongwook Lee, Won-Jin Moon, Jong Chul Ye:
Which Contrast Does Matter? Towards a Deep Understanding of MR Contrast using Collaborative GAN. CoRR abs/1905.04105 (2019) - [i42]Yoseob Han, Junyoung Kim, Jong Chul Ye:
Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal. CoRR abs/1906.06854 (2019) - [i41]Eunju Cha, Jaeduck Jang, Junho Lee, Eunha Lee, Jong Chul Ye:
Boosting CNN beyond Label in Inverse Problems. CoRR abs/1906.07330 (2019) - [i40]Boah Kim, Jieun Kim, June-Goo Lee, Dong Hwan Kim, Seong Ho Park, Jong Chul Ye:
Unsupervised Deformable Image Registration Using Cycle-Consistent CNN. CoRR abs/1907.01319 (2019) - [i39]Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Adaptive and Compressive Beamforming using Deep Learning for Medical Ultrasound. CoRR abs/1907.10257 (2019) - [i38]Sungjun Lim, Sang-Eun Lee, Sunghoe Chang, Jong Chul Ye:
CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry. CoRR abs/1908.09414 (2019) - [i37]Byeongsu Sim, Gyutaek Oh, Sungjun Lim, Jong Chul Ye:
Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems. CoRR abs/1909.12116 (2019) - [i36]Mathews Jacob, Merry P. Mani, Jong Chul Ye:
Structured Low-Rank Algorithms: Theory, MR Applications, and Links to Machine Learning. CoRR abs/1910.12162 (2019) - 2018
- [j38]Jae Jun Yoo, Abdul Wahab, Jong Chul Ye:
A Mathematical Framework for Deep Learning in Elastic Source Imaging. SIAM J. Appl. Math. 78(5): 2791-2818 (2018) - [j37]Jong Chul Ye, Yoseob Han, Eunju Cha:
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems. SIAM J. Imaging Sci. 11(2): 991-1048 (2018) - [j36]Dongwook Lee, Jae Jun Yoo, Sungho Tak, Jong Chul Ye:
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks. IEEE Trans. Biomed. Eng. 65(9): 1985-1995 (2018) - [j35]Kyong Hwan Jin, Jong Chul Ye:
Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal. IEEE Trans. Image Process. 27(3): 1448-1461 (2018) - [j34]Junhong Min, Kyong Hwan Jin, Michael Unser, Jong Chul Ye:
Grid-Free Localization Algorithm Using Low-Rank Hankel Matrix for Super-Resolution Microscopy. IEEE Trans. Image Process. 27(10): 4771-4786 (2018) - [j33]Kiryung Lee, Yanjun Li, Kyong Hwan Jin, Jong Chul Ye:
Unified Theory for Recovery of Sparse Signals in a General Transform Domain. IEEE Trans. Inf. Theory 64(8): 5457-5477 (2018) - [j32]Ge Wang, Jong Chul Ye, Klaus Mueller, Jeffrey A. Fessler:
Image Reconstruction is a New Frontier of Machine Learning. IEEE Trans. Medical Imaging 37(6): 1289-1296 (2018) - [j31]Eunhee Kang, Won Chang, Jae Jun Yoo, Jong Chul Ye:
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network. IEEE Trans. Medical Imaging 37(6): 1358-1369 (2018) - [j30]Yoseob Han, Jong Chul Ye:
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT. IEEE Trans. Medical Imaging 37(6): 1418-1429 (2018) - [c68]Yeo Hun Yoon, Jong Chul Ye:
Deep Learning for Accelerated Ultrasound Imaging. ICASSP 2018: 6673-6676 - [c67]Eunhee Kang, Jong Chul Ye:
Framelet denoising for low-dose CT using deep learning. ISBI 2018: 311-314 - [c66]Eunju Cha, Eung-Yeop Kim, Jong Chul Ye:
Improved Time-Resolved MRA Using k-Space Deep Learning. MLMIR@MICCAI 2018: 47-54 - [i35]Yoseob Han, Jingu Kang, Jong Chul Ye:
Deep Learning Reconstruction for 9-View Dual Energy CT Baggage Scanner. CoRR abs/1801.01258 (2018) - [i34]Jae Jun Yoo, Abdul Wahab, Jong Chul Ye:
A Mathematical Framework for Deep Learning in Elastic Source Imaging. CoRR abs/1802.10055 (2018) - [i33]Dongwook Lee, Jae Jun Yoo, Sungho Tak, Jong Chul Ye:
Deep Residual Learning for Accelerated MRI using Magnitude and Phase Networks. CoRR abs/1804.00432 (2018) - [i32]Hyun-Seo Ahn, Sunghong Park, Jong Chul Ye:
Quantitative Susceptibility Map Reconstruction Using Annihilating Filter-based Low-Rank Hankel Matrix Approach. CoRR abs/1804.09396 (2018) - [i31]Yoseob Han, Jong Chul Ye:
k-Space Deep Learning for Accelerated MRI. CoRR abs/1805.03779 (2018) - [i30]Juyoung Lee, Yoseob Han, Jong Chul Ye:
k-Space Deep Learning for Reference-free EPI Ghost Correction. CoRR abs/1806.00153 (2018) - [i29]Eunju Cha, Eung-Yeop Kim, Jong Chul Ye:
k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography. CoRR abs/1806.00806 (2018) - [i28]Eunhee Kang, Hyun Jung Koo, Dong Hyun Yang, Joon Bum Seo, Jong Chul Ye:
Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography. CoRR abs/1806.09748 (2018) - [i27]Kyong Hwan Jin, Gain Kim, Yusuf Leblebici, Jong Chul Ye, Michael Unser:
Direct Reconstruction of Saturated Samples in Band-Limited OFDM Signals. CoRR abs/1809.07188 (2018) - [i26]Yoseob Han, Jong Chul Ye:
One Network to Solve All ROIs: Deep Learning CT for Any ROI using Differentiated Backprojection. CoRR abs/1810.00500 (2018) - 2017
- [j29]Jae Jun Yoo, Younghoon Jung, Mikyoung Lim, Jong Chul Ye, Abdul Wahab:
A Joint Sparse Recovery Framework for Accurate Reconstruction of Inclusions in Elastic Media. SIAM J. Imaging Sci. 10(3): 1104-1138 (2017) - [j28]Jong Chul Ye, Jongmin Kim, Kyong Hwan Jin, Kiryung Lee:
Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation. IEEE Trans. Inf. Theory 63(2): 777-801 (2017) - [c65]Radu Timofte, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, Lei Zhang, Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, Kyoung Mu Lee, Xintao Wang, Yapeng Tian, Ke Yu, Yulun Zhang, Shixiang Wu, Chao Dong, Liang Lin, Yu Qiao, Chen Change Loy, Woong Bae, Jae Jun Yoo, Yoseob Han, Jong Chul Ye, Jae-Seok Choi, Munchurl Kim, Yuchen Fan, Jiahui Yu, Wei Han, Ding Liu, Haichao Yu, Zhangyang Wang, Honghui Shi, Xinchao Wang, Thomas S. Huang, Yunjin Chen, Kai Zhang, Wangmeng Zuo, Zhimin Tang, Linkai Luo, Shaohui Li, Min Fu, Lei Cao, Wen Heng, Giang Bui, Truc Le, Ye Duan, Dacheng Tao, Ruxin Wang, Xu Lin, Jianxin Pang, Jinchang Xu, Yu Zhao, Xiangyu Xu, Jin-shan Pan, Deqing Sun, Yujin Zhang, Xibin Song, Yuchao Dai, Xueying Qin, Xuan-Phung Huynh, Tiantong Guo, Hojjat Seyed Mousavi, Tiep Huu Vu, Vishal Monga, Cristóvão Cruz, Karen O. Egiazarian, Vladimir Katkovnik, Rakesh Mehta, Arnav Kumar Jain, Abhinav Agarwalla, Ch V. Sai Praveen, Ruofan Zhou, Hongdiao Wen, Che Zhu, Zhiqiang Xia, Zhengtao Wang, Qi Guo:
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results. CVPR Workshops 2017: 1110-1121 - [c64]Woong Bae, Jae Jun Yoo, Jong Chul Ye:
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification. CVPR Workshops 2017: 1141-1149 - [c63]Dongwook Lee, Jae Jun Yoo, Jong Chul Ye:
Deep residual learning for compressed sensing MRI. ISBI 2017: 15-18 - [i25]Dongwook Lee, Jae Jun Yoo, Jong Chul Ye:
Deep artifact learning for compressed sensing and parallel MRI. CoRR abs/1703.01120 (2017) - [i24]Yoseob Han, Jae Jun Yoo, Jong Chul Ye:
Deep Learning with Domain Adaptation for Accelerated Projection Reconstruction MR. CoRR abs/1703.01135 (2017) - [i23]Jawook Gu, Jong Chul Ye:
Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction. CoRR abs/1703.01382 (2017) - [i22]Eunhee Kang, Junhong Min, Jong Chul Ye:
Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction. CoRR abs/1703.01383 (2017) - [i21]Jae Hyun Lim, Jong Chul Ye:
Geometric GAN. CoRR abs/1705.02894 (2017) - [i20]Jong Chul Ye, Yoseob Han:
Deep Convolutional Framelets: A General Deep Learning for Inverse Problems. CoRR abs/1707.00372 (2017) - [i19]Eunhee Kang, Jae Jun Yoo, Jong Chul Ye:
Wavelet Residual Network for Low-Dose CT via Deep Convolutional Framelets. CoRR abs/1707.09938 (2017) - [i18]