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NTIS 바로가기Proceedings of the IEEE, v.108 no.1, 2020년, pp.86 - 109
Ravishankar, Saiprasad (Michigan State University, East Lansing, USA) , Ye, Jong Chul (Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea) , Fessler, Jeffrey A. (University of Michigan, Ann Arbor, USA)
The field of medical image reconstruction has seen roughly four types of methods. The first type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray computed tomography (CT) and the inverse Fourier transform for magnetic resonance imaging (MRI), based on simple mathemati...
Yoon, Yeo Hun, Khan, Shujaat, Huh, Jaeyoung, Ye, Jong Chul. Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning. IEEE transactions on medical imaging, vol.38, no.2, 325-336.
Nehme, Elias, Weiss, Lucien E., Michaeli, Tomer, Shechtman, Yoav. Deep-STORM: super-resolution single-molecule microscopy by deep learning. Optica, vol.5, no.4, 458-.
Rivenson, Yair, Göröcs, Zoltán, Günaydin, Harun, Zhang, Yibo, Wang, Hongda, Ozcan, Aydogan. Deep learning microscopy. Optica, vol.4, no.11, 1437-.
510k Premarket Notification of AiCE Deep Learning Reconstruction (Canon) 2019
Sinha, Ayan, Lee, Justin, Li, Shuai, Barbastathis, George. Lensless computational imaging through deep learning. Optica, vol.4, no.9, 1117-.
McCollough, Cynthia H., Bartley, Adam C., Carter, Rickey E., Chen, Baiyu, Drees, Tammy A., Edwards, Phillip, Holmes III, David R., Huang, Alice E., Khan, Farhana, Leng, Shuai, McMillan, Kyle L., Michalak, Gregory J., Nunez, Kristina M., Yu, Lifeng, Fletcher, Joel G.. Low‐dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge. Medical physics, vol.44, no.10,
510k Premarket Notification of Deep Learning Image Reconstruction (GE Medical Systems) 2019
Kwon, Kinam, Kim, Dongchan, Park, HyunWook. A parallel MR imaging method using multilayer perceptron. Medical physics, vol.44, no.12, 6209-6224.
arXiv 1811 08839 fastMRI: An open dataset and benchmarks for accelerated MRI zbontar 2018
Gong, Kuang, Catana, Ciprian, Qi, Jinyi, Li, Quanzheng. PET Image Reconstruction Using Deep Image Prior. IEEE transactions on medical imaging, vol.38, no.7, 1655-1665.
Luchies, Adam C., Byram, Brett C.. Deep Neural Networks for Ultrasound Beamforming. IEEE transactions on medical imaging, vol.37, no.9, 2010-2021.
Floyd Jr., C.E.. An artificial neural network for SPECT image reconstruction. IEEE transactions on medical imaging, vol.10, no.3, 485-487.
Wang, Ge, Ye, Jong Chu, Mueller, Klaus, Fessler, Jeffrey A.. Image Reconstruction is a New Frontier of Machine Learning. IEEE transactions on medical imaging, vol.37, no.6, 1289-1296.
Schlemper, Jo, Caballero, Jose, Hajnal, Joseph V., Price, Anthony N., Rueckert, Daniel. A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction. IEEE transactions on medical imaging, vol.37, no.2, 491-503.
Moore, Brian E., Ravishankar, Saiprasad, Nadakuditi, Raj Rao, Fessler, Jeffrey A.. Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models. IEEE transactions on computational imaging, vol.6, 153-166.
Mardani, Morteza, Mateos, Gonzalo, Giannakis, Georgios B.. Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.63, no.10, 2663-2677.
Gleichman, S., Eldar, Y. C.. Blind Compressed Sensing. IEEE transactions on information theory, vol.57, no.10, 6958-6975.
Shan, Hongming, Padole, Atul, Homayounieh, Fatemeh, Kruger, Uwe, Khera, Ruhani Doda, Nitiwarangkul, Chayanin, Kalra, Mannudeep K., Wang, Ge. Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction. Nature machine intelligence, vol.1, no.6, 269-276.
Wang, Ge. A Perspective on Deep Imaging. IEEE access : practical research, open solutions, vol.4, 8914-8924.
Lee, Dongwook, Yoo, Jaejun, Tak, Sungho, Ye, Jong Chul. Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks. IEEE transactions on bio-medical engineering, vol.65, no.9, 1985-1995.
Yang, Qingsong, Yan, Pingkun, Zhang, Yanbo, Yu, Hengyong, Shi, Yongyi, Mou, Xuanqin, Kalra, Mannudeep K., Zhang, Yi, Sun, Ling, Wang, Ge. Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss. IEEE transactions on medical imaging, vol.37, no.6, 1348-1357.
arXiv 1712 02862 MoDL: Model based deep learning architecture for inverse problems aggarwal 2017
Chen, Hu, Zhang, Yi, Chen, Yunjin, Zhang, Junfeng, Zhang, Weihua, Sun, Huaiqiang, Lv, Yang, Liao, Peixi, Zhou, Jiliu, Wang, Ge. LEARN: Learned Experts’ Assessment-Based Reconstruction Network for Sparse-Data CT. IEEE transactions on medical imaging, vol.37, no.6, 1333-1347.
Quan, Tran Minh, Nguyen-Duc, Thanh, Jeong, Won-Ki. Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss. IEEE transactions on medical imaging, vol.37, no.6, 1488-1497.
arXiv 1709 01809 CNN-based projected gradient descent for consistent image reconstruction gupta 2017
Beck, Amir, Teboulle, Marc. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. SIAM journal on imaging sciences, vol.2, no.1, 183-202.
Proc 27th Int Conf Int Conf Mach Learn Learning fast approximations of sparse coding gregor 2010 399
arXiv 1710 03344 Iterative PET image reconstruction using convolutional neural network representation gong 2017
Wu, Dufan, Kim, Kyungsang, El Fakhri, Georges, Li, Quanzheng. Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network. IEEE transactions on medical imaging, vol.36, no.12, 2479-2486.
Lingala, S. G., Jacob, M.. Blind Compressive Sensing Dynamic MRI. IEEE transactions on medical imaging, vol.32, no.6, 1132-1145.
Ravishankar, Saiprasad, Bresler, Yoram. MR Image Reconstruction From Highly Undersampled k-Space Data by Dictionary Learning. IEEE transactions on medical imaging, vol.30, no.5, 1028-1041.
Chen, Hu, Zhang, Yi, Zhang, Weihua, Liao, Peixi, Li, Ke, Zhou, Jiliu, Wang, Ge. aLow-dose CT via convolutional neural network. Biomedical optics express, vol.8, no.2, 679-.
Ravishankar, Saiprasad, Bresler, Yoram. Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing. IEEE transactions on computational imaging, vol.2, no.3, 294-309.
Qu, Xiaobo, Zhang, Weiru, Guo, Di, Cai, Congbo, Cai, Shuhui, Chen, Zhong. Iterative thresholding compressed sensing MRI based on contourlet transform. Inverse problems in science and engineering, vol.18, no.6, 737-758.
Donghwan Kim, Ramani, Sathish, Fessler, Jeffrey A.. Combining Ordered Subsets and Momentum for Accelerated X-Ray CT Image Reconstruction. IEEE transactions on medical imaging, vol.34, no.1, 167-178.
arXiv 1302 0561 Breaking the coherence barrier: A new theory for compressed sensing adcock 2013
Ravishankar, S., Bresler, Y.. Learning Sparsifying Transforms. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.61, no.5, 1072-1086.
Aharon, M., Elad, M., Bruckstein, A.. K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.54, no.11, 4311-4322.
Zheng, Xuehang, Ravishankar, Saiprasad, Long, Yong, Fessler, Jeffrey A.. PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction. IEEE transactions on medical imaging, vol.37, no.6, 1498-1510.
IEEE Trans Med Imag Low-dose X-ray CT reconstruction via dictionary learning xu 2012 10.1109/TMI.2012.2195669 31 1682
Ahn, Sangtae, Ross, Steven G, Asma, Evren, Miao, Jun, Jin, Xiao, Cheng, Lishui, Wollenweber, Scott D, Manjeshwar, Ravindra M. Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET. Physics in medicine & biology, vol.60, no.15, 5733-5751.
Bouman, C., Sauer, K.. A generalized Gaussian image model for edge-preserving MAP estimation. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.2, no.3, 296-310.
Proc 18th Int Conf Med Image Comput -Assist Intervent U-net: Convolutional networks for biomedical image segmentation ronneberger 2015 234
Kang, Eunhee, Min, Junhong, Ye, Jong Chul. A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction. Medical physics, vol.44, no.10,
Zhang, Kai, Zuo, Wangmeng, Chen, Yunjin, Meng, Deyu, Zhang, Lei. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.26, no.7, 3142-3155.
arXiv 1906 00165 Multi-layer residual sparsifying transform learning for image reconstruction zheng 2019
Proc Adv Neural Inf Process Syst ImageNet classification with deep convolutional neural networks krizhevsky 2012 1097
arXiv 1802 05584 Convolutional analysis operator learning: Acceleration and convergence chun 2018
Proc SPIE Learning sparsifying filter banks pfister 2015 9597 959703-1
Compressed Sens geerts-ossevoort 2018
Liang, Zhi-Pei, Haacke, E M, Thomas, C W. High-resolution inversion of finite Fourier transform data through a localised polynomial approximation. Inverse problems, vol.5, no.5, 831-847.
Leahy, R.M., Jeffs, B.D.. On the design of maximally sparse beamforming arrays. IEEE transactions on antennas and propagation, vol.39, no.8, 1178-1187.
Thibault, Jean‐Baptiste, Sauer, Ken D., Bouman, Charles A., Hsieh, Jiang. A three‐dimensional statistical approach to improved image quality for multislice helical CT. Medical physics, vol.34, no.11, 4526-4544.
Nuyts, J., Beque, D., Dupont, P., Mortelmans, L.. A concave prior penalizing relative differences for maximum-a-posteriori reconstruction in emission tomography. IEEE transactions on nuclear science, vol.49, no.1, 56-60.
Fessler, J.A., Rogers, W.L.. Spatial resolution properties of penalized-likelihood image reconstruction: space-invariant tomographs. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.5, no.9, 1346-1358.
Proc Int Soc Mag Res Med A neural network approach to NMR spectral estimation venkataraman 1994 1214
Gong, Kuang, Guan, Jiahui, Kim, Kyungsang, Zhang, Xuezhu, Yang, Jaewon, Seo, Youngho, El Fakhri, Georges, Qi, Jinyi, Li, Quanzheng. Iterative PET Image Reconstruction Using Convolutional Neural Network Representation. IEEE transactions on medical imaging, vol.38, no.3, 675-685.
Nature Image reconstruction by domain-transform manifold learning zhu 2018 10.1038/nature25988 555 487
Han, Yoseob, Yoo, Jaejun, Kim, Hak Hee, Shin, Hee Jung, Sung, Kyunghyun, Ye, Jong Chul. Deep learning with domain adaptation for accelerated projection‐reconstruction MR. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.80, no.3, 1189-1205.
Hammernik, Kerstin, Klatzer, Teresa, Kobler, Erich, Recht, Michael P., Sodickson, Daniel K., Pock, Thomas, Knoll, Florian. Learning a variational network for reconstruction of accelerated MRI data. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.79, no.6, 3055-3071.
Han, Yoseob, Ye, Jong Chul. Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT. IEEE transactions on medical imaging, vol.37, no.6, 1418-1429.
Jin, Kyong Hwan, McCann, Michael T., Froustey, Emmanuel, Unser, Michael. Deep Convolutional Neural Network for Inverse Problems in Imaging. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.26, no.9, 4509-4522.
Wolterink, Jelmer M., Leiner, Tim, Viergever, Max A., Isgum, Ivana. Generative Adversarial Networks for Noise Reduction in Low-Dose CT. IEEE transactions on medical imaging, vol.36, no.12, 2536-2545.
Sauer, K., Bouman, C.. A local update strategy for iterative reconstruction from projections. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.41, no.2, 534-548.
De Pierro, A.R.. On the relation between the ISRA and the EM algorithm for positron emission tomography. IEEE transactions on medical imaging, vol.12, no.2, 328-333.
Adler, Jonas, Öktem, Ozan. Learned Primal-Dual Reconstruction. IEEE transactions on medical imaging, vol.37, no.6, 1322-1332.
Pruessmann, Klaas P.. Encoding and reconstruction in parallel MRI. NMR in biomedicine, vol.19, no.3, 288-299.
Hudson, H.M., Larkin, R.S.. Accelerated image reconstruction using ordered subsets of projection data. IEEE transactions on medical imaging, vol.13, no.4, 601-609.
Chen, Hu, Zhang, Yi, Kalra, Mannudeep K., Lin, Feng, Chen, Yang, Liao, Peixi, Zhou, Jiliu, Wang, Ge. Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network. IEEE transactions on medical imaging, vol.36, no.12, 2524-2535.
Kang, Eunhee, Chang, Won, Yoo, Jaejun, Ye, Jong Chul. Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network. IEEE transactions on medical imaging, vol.37, no.6, 1358-1369.
Gindi, G., Lee, M., Rangarajan, A., Zubal, I.G.. Bayesian reconstruction of functional images using anatomical information as priors. IEEE transactions on medical imaging, vol.12, no.4, 670-680.
Chen, C.-T., Ouyang, X., Wong, W.H., Hu, X., Johnson, V.E., Ordonez, C., Metz, C.E.. Sensor fusion in image reconstruction. IEEE transactions on nuclear science, vol.38, no.2, 687-692.
Liang, Z.-P., Lauterbur, P.C.. A generalized series approach to MR spectroscopic imaging. IEEE transactions on medical imaging, vol.10, no.2, 132-137.
Cao, Yue, Levin, David N.. Using prior knowledge of human anatomy to constrain MR image acquisition and reconstruction: Half k-space and full k-space techniques. Magnetic resonance imaging, vol.15, no.6, 669-677.
Geman, Stuart, Geman, Donald. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. IEEE transactions on pattern analysis and machine intelligence, vol.pami6, no.6, 721-741.
Pruessmann, Klaas P., Weiger, Markus, Börnert, Peter, Boesiger, Peter. Advances in sensitivity encoding with arbitrary k-space trajectories. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.46, no.4, 638-651.
Kao, Chien-Min, Pan, Xiaochuan, Chen, Chin-Tu, Wong, Wing H.. Image restoration and reconstruction with a Bayesian approach. Medical physics, vol.25, no.5, 600-613.
Besag, Julian. On the Statistical Analysis of Dirty Pictures. Journal of the Royal Statistical Society. Series B (Methodological), vol.48, no.3, 259-279.
Hu, Yuxin, Levine, Evan G., Tian, Qiyuan, Moran, Catherine J., Wang, Xiaole, Taviani, Valentina, Vasanawala, Shreyas S., McNab, Jennifer A., Daniel, Bruce A., Hargreaves, Brian L.. Motion‐robust reconstruction of multishot diffusion‐weighted images without phase estimation through locally low‐rank regularization. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.81, no.2, 1181-1190.
Magn Reson Med Accelerating functional MRI using fixed-rank approximations and radial-Cartesian sampling chiew 2016 10.1002/mrm.26079 76 1825
Lima da Cruz, Gastão, Bustin, Aurélien, Jaubert, Oliver, Schneider, Torben, Botnar, René M., Prieto, Claudia. Sparsity and locally low rank regularization for MR fingerprinting. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.81, no.6, 3530-3543.
Mazor, Gal, Weizman, Lior, Tal, Assaf, Eldar, Yonina C.. Low‐rank magnetic resonance fingerprinting. Medical physics, vol.45, no.9, 4066-4084.
Zhao, Bo, Setsompop, Kawin, Adalsteinsson, Elfar, Gagoski, Borjan, Ye, Huihui, Ma, Dan, Jiang, Yun, Ellen Grant, P., Griswold, Mark A., Wald, Lawrence L.. Improved magnetic resonance fingerprinting reconstruction with low‐rank and subspace modeling. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.79, no.2, 933-942.
Pedersen, Henrik, Kozerke, Sebastian, Ringgaard, Steffen, Nehrke, Kay, Kim, Won Yong. k-t PCA: Temporally constrained k-t BLAST reconstruction using principal component analysis. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.62, no.3, 706-716.
Chen, Guang-Hong, Tang, Jie, Leng, Shuai. Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets : Prior image constrained compressed sensing (PICCS). Medical physics, vol.35, no.2, 660-663.
Liu, Yunsong, Zhan, Zhifang, Cai, Jian-Feng, Guo, Di, Chen, Zhong, Qu, Xiaobo. Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging. IEEE transactions on medical imaging, vol.35, no.9, 2130-2140.
Liu, Yunsong, Cai, Jian-Feng, Zhan, Zhifang, Guo, Di, Ye, Jing, Chen, Zhong, Qu, Xiaobo. Balanced Sparse Model for Tight Frames in Compressed Sensing Magnetic Resonance Imaging. PloS one, vol.10, no.4, e0119584-.
Haldar, Justin P..
Low-Rank Modeling of Local
Kyong Hwan Jin, Dongwook Lee, Jong Chul Ye. A General Framework for Compressed Sensing and Parallel MRI Using Annihilating Filter Based Low-Rank Hankel Matrix. IEEE transactions on computational imaging, vol.2, no.4, 480-495.
Lee, Dongwook, Jin, Kyong Hwan, Kim, Eung Yeop, Park, Sung‐Hong, Ye, Jong Chul. Acceleration of MR parameter mapping using annihilating filter‐based low rank hankel matrix (ALOHA). Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.76, no.6, 1848-1864.
Ongie, Greg, Jacob, Mathews. Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier Samples. SIAM journal on imaging sciences, vol.9, no.3, 1004-1041.
Ongie, Gregory, Jacob, Mathews. A Fast Algorithm for Convolutional Structured Low-Rank Matrix Recovery. IEEE transactions on computational imaging, vol.3, no.4, 535-550.
Jin, Kyong Hwan, Um, Ji‐Yong, Lee, Dongwook, Lee, Juyoung, Park, Sung‐Hong, Ye, Jong Chul. MRI artifact correction using sparse + low‐rank decomposition of annihilating filter‐based hankel matrix. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.78, no.1, 327-340.
Chandrasekaran, Venkat, Recht, Benjamin, Parrilo, Pablo A., Willsky, Alan S.. The Convex Geometry of Linear Inverse Problems. Foundations of computational mathematics, vol.12, no.6, 805-849.
Lee, Juyoung, Han, Yoseob, Ryu, Jae‐Kyun, Park, Jang‐Yeon, Ye, Jong Chul. k‐Space deep learning for reference‐free EPI ghost correction. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.82, no.6, 2299-2313.
Akçakaya, Mehmet, Moeller, Steen, Weingärtner, Sebastian, Uğurbil, Kâmil. Scan‐specific robust artificial‐neural‐networks for k‐space interpolation (RAKI) reconstruction: Database‐free deep learning for fast imaging. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.81, no.1, 439-453.
Han, Yoseob, Ye, Jong Chul. One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection. Medical physics, vol.46, no.12,
Ghani, Muhammad Usman, Karl, W. Clem. Deep Learning Based Sinogram Correction for Metal Artifact Reduction. IS&T International Symposium on Electronic Imaging, vol.2018, no.15, 472-1-4728.
Lee, Hoyeon, Lee, Jongha, Kim, Hyeongseok, Cho, Byungchul, Cho, Seungryong. Deep-Neural-Network-Based Sinogram Synthesis for Sparse-View CT Image Reconstruction. IEEE transactions on radiation and plasma medical sciences, vol.3, no.2, 109-119.
IEEE Trans Med Imag k-space deep learning for accelerated MRI han 0
Maravic, I., Vetterli, M.. Sampling and reconstruction of signals with finite rate of innovation in the presence of noise. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.53, no.8, 2788-2805.
Vetterli, M., Marziliano, P., Blu, T.. Sampling signals with finite rate of innovation. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.50, no.6, 1417-1428.
Proc IEEE Conf Comput Vis Pattern Recognit Deep image prior ulyanov 2018 9446
Ongie, Greg, Biswas, Sampurna, Jacob, Mathews. Convex Recovery of Continuous Domain Piecewise Constant Images From Nonuniform Fourier Samples. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.66, no.1, 236-250.
Proc Int Conf Med Image Comput Comput -Assist Intervent Deep learning computed tomography würfl 2016 432
Ye, Jong Chul, Kim, Jong Min, Jin, Kyong Hwan, Lee, Kiryung. Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation. IEEE transactions on information theory, vol.63, no.2, 777-801.
arXiv 1904 04691 Fast enhanced CT metal artifact reduction using data domain deep learning ghani 2019
Lee, Juyoung, Jin, Kyong Hwan, Ye, Jong Chul. Reference‐free single‐pass EPI Nyquist ghost correction using annihilating filter‐based low rank Hankel matrix (ALOHA). Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.76, no.6, 1775-1789.
Christodoulou, Anthony G., Shaw, Jaime L., Nguyen, Christopher, Yang, Qi, Xie, Yibin, Wang, Nan, Li, Debiao. Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging. Nature biomedical engineering, vol.2, no.4, 215-226.
Min, Junhong, Jin, Kyong Hwan, Unser, Michael, Ye, Jong Chul. Grid-Free Localization Algorithm Using Low-Rank Hankel Matrix for Super-Resolution Microscopy. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.27, no.10, 4771-4786.
Kyong Hwan Jin, Jong Chul Ye. Annihilating Filter-Based Low-Rank Hankel Matrix Approach for Image Inpainting. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.24, no.11, 3498-3511.
Haacke, E.M., Liang, Z.-P., Izen, S.H.. Superresolution reconstruction through object modeling and parameter estimation. IEEE transactions on acoustics, speech, and signal processing, vol.37, no.4, 592-595.
Shin, Peter J., Larson, Peder E. Z., Ohliger, Michael A., Elad, Michael, Pauly, John M., Vigneron, Daniel B., Lustig, Michael. Calibrationless parallel imaging reconstruction based on structured low‐rank matrix completion. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.72, no.4, 959-970.
Bo Zhao, Haldar, J. P., Christodoulou, A. G., Zhi-Pei Liang. Image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints. IEEE transactions on medical imaging, vol.31, no.9, 1809-1820.
Lingala, Sajan Goud, Yue Hu, DiBella, Edward, Jacob, Mathews. Accelerated Dynamic MRI Exploiting Sparsity and Low-Rank Structure: k-t SLR. IEEE transactions on medical imaging, vol.30, no.5, 1042-1054.
Han Guo, Chenlu Qiu, Vaswani, Namrata. An Online Algorithm for Separating Sparse and Low-Dimensional Signal Sequences From Their Sum. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.62, no.16, 4284-4297.
Candès, Emmanuel J., Li, Xiaodong, Ma, Yi, Wright, John. Robust principal component analysis?. Journal of the Association for Computing Machinery, vol.58, no.3, 1-37.
Proc ISMRM Local versus global low-rank promotion in dynamic MRI series reconstruction trzasko 2011 4371
He, Jingfei, Liu, Qiegen, Christodoulou, Anthony G., Ma, Chao, Lam, Fan, Liang, Zhi-Pei. Accelerated High-Dimensional MR Imaging With Sparse Sampling Using Low-Rank Tensors. IEEE transactions on medical imaging, vol.35, no.9, 2119-2129.
Otazo, Ricardo, Candès, Emmanuel, Sodickson, Daniel K.. Low‐rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.73, no.3, 1125-1136.
Tremoulheac, Benjamin, Dikaios, Nikolaos, Atkinson, David, Arridge, Simon R..
Dynamic MR Image Reconstruction–Separation From Undersampled (
Kang, Eunhee, Koo, Hyun Jung, Yang, Dong Hyun, Seo, Joon Bum, Ye, Jong Chul. Cycle‐consistent adversarial denoising network for multiphase coronary CT angiography. Medical physics, vol.46, no.2, 550-562.
Qu, X., Guo, D., Ning, B., Hou, Y., Lin, Y., Cai, S., Chen, Z.. Undersampled MRI reconstruction with patch-based directional wavelets. Magnetic resonance imaging, vol.30, no.7, 964-977.
Jin, Kyong Hwan, Ye, Jong Chul. Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.27, no.3, 1448-1461.
arXiv 1808 08791 SPULTRA: Low-dose CT image reconstruction with joint statistical and learned image models ye 2018
Candès, Emmanuel, Demanet, Laurent, Donoho, David, Ying, Lexing. Fast Discrete Curvelet Transforms. Multiscale modeling & simulation, vol.5, no.3, 861-899.
Do, M.N., Vetterli, M.. The Contourlet Transform: An Efficient Directional Multiresolution Image Representation. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.14, no.12, 2091-2106.
Duffin, R. J., Schaeffer, A. C.. A class of nonharmonic Fourier series. Transactions of the American Mathematical Society, vol.72, no.2, 341-366.
Yin, Rujie, Gao, Tingran, Lu, Yue M., Daubechies, Ingrid. A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets. SIAM journal on imaging sciences, vol.10, no.2, 711-750.
Barrett, Harrison H., Abbey, Craig K., Clarkson, Eric. Objective assessment of image quality III ROC metrics, ideal observers, and likelihood-generating functions. Journal of the Optical Society of America. A, Optics, image science, and vision, vol.15, no.6, 1520-.
Zhou Wang, Bovik, A.C.. Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures. IEEE signal processing magazine, vol.26, no.1, 98-117.
Ye, Jong Chul, Han, Yoseob, Cha, Eunju. Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems. SIAM journal on imaging sciences, vol.11, no.2, 991-1048.
Proceedings 36th Int Conf Mach Learn Understanding geometry of encoder-decoder CNNs ye 2019 97 7064
Gözcü, Baran, Mahabadi, Rabeeh Karimi, Li, Yen-Huan, Ilıcak, Efe, Çukur, Tolga, Scarlett, Jonathan, Cevher, Volkan. Learning-Based Compressive MRI. IEEE transactions on medical imaging, vol.37, no.6, 1394-1406.
Proc Int Conf Mach Learn Optimization landscape and expressivity of deep CNNs nguyen 2018 3727
Proc Adv Neural Inf Process Syst On the optimization landscape of tensor decompositions ge 2017 3653
Proc Int Conf Mach Learn Gradient descent learns one-hidden-layer CNN: Don’t be afraid of spurious local minima du 2018 1338
Proc Adv Neural Inf Process Syst Implicit bias of gradient descent on linear convolutional networks gunasekar 2018 9461
J Mach Learn Res The implicit bias of gradient descent on separable data soudry 2018 19 2822
arXiv 1903 11431 Transform learning for magnetic resonance image reconstruction: From model-based learning to building neural networks wen 2019
Ravishankar, Saiprasad, Bresler, Yoram. Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging. SIAM journal on imaging sciences, vol.8, no.4, 2519-2557.
Chun, Il Yong, Fessler, Jeffrey A.. Convolutional Dictionary Learning: Acceleration and Convergence. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.27, no.4, 1697-1712.
Wohlberg, Brendt. Efficient Algorithms for Convolutional Sparse Representations. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.25, no.1, 301-315.
Tanc, A.K., Eksioglu, E.M.. MRI reconstruction with joint global regularization and transform learning. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, vol.53, 1-8.
Proc SPIE Model-based iterative tomographic reconstruction with adaptive sparsifying transforms pfister 2014 9020 90200h-1
Wen, Bihan, Ravishankar, Saiprasad, Bresler, Yoram. Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications. International journal of computer vision, vol.114, no.2, 137-167.
Segars, W. P., Mahesh, M., Beck, T. J., Frey, E. C., Tsui, B. M. W.. Realistic CT simulation using the 4D XCAT phantom : Realistic CT simulation using the 4D XCAT phantom. Medical physics, vol.35, no.8, 3800-3808.
Proc IEEE 27th Int Workshop Mach Learn Signal Process (MLSP) Adaptive sparse modeling and shifted-Poisson likelihood based approach for low-dose CT image reconstruction ye 2017 1
arXiv 1901 00106 DECT-MULTRA: Dual-energy CT image decomposition with learned mixed material models and efficient clustering li 2019
Jang Hwan Cho, Fessler, Jeffrey A.. Regularization Designs for Uniform Spatial Resolution and Noise Properties in Statistical Image Reconstruction for 3-D X-ray CT. IEEE transactions on medical imaging, vol.34, no.2, 678-689.
Wen, Bihan, Ravishankar, Saiprasad, Bresler, Yoram. FRIST—flipping and rotation invariant sparsifying transform learning and applications. Inverse problems, vol.33, no.7, 074007-.
Proc SPIE Image-domain multi-material decomposition using a union of cross-material models li 2019 11072 1107210-1
arXiv 1808 01316 The power of complementary regularizers: Image recovery via transform learning and low-rank modeling wen 2018
Dabov, Kostadin, Foi, Alessandro, Katkovnik, Vladimir, Egiazarian, Karen. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.16, no.8, 2080-2095.
Proc Adv Neural Inf Process Syst Deep ADMM-net for compressive sensing MRI yang 2016 10
arXiv 1609 04104 Tracking tensor subspaces with informative random sampling for real-time MR imaging mardani 2016
Fessler, J.A., Sutton, B.P.. Nonuniform fast Fourier transforms using min-max interpolation. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.51, no.2, 560-574.
Pfister, Luke, Bresler, Yoram. Learning Filter Bank Sparsifying Transforms. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.67, no.2, 504-519.
Feldkamp, L. A., Davis, L. C., Kress, J. W.. Practical cone-beam algorithm. Journal of the Optical Society of America. A, Optics and image science, vol.1, no.6, 612-.
Proc IEEE Asilomar Conf Signals Syst Comput Convolutional analysis operator learning: Application to sparse-view CT chun 2018 1631
Elad, Michael, Aharon, Michal. Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.15, no.12, 3736-3745.
J Mach Learn Res Online learning for matrix factorization and sparse coding mairal 2010 11 19
Olshausen, Bruno A., Field, David J.. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, vol.381, no.6583, 607-609.
Vidal, René. Subspace Clustering. IEEE signal processing magazine, vol.28, no.2, 52-68.
Mag Res Med Low-dimensional-structure self-learning and thresholding: Regularization beyond compressed sensing for MRI reconstruction akcakaya 2011 10.1002/mrm.22841 66 756
Qu, X., Hou, Y., Lam, F., Guo, D., Zhong, J., Chen, Z.. Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator. Medical image analysis, vol.18, no.6, 843-856.
Zhan, Zhifang, Cai, Jian-Feng, Guo, Di, Liu, Yunsong, Chen, Zhong, Qu, Xiaobo. Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction. IEEE transactions on bio-medical engineering, vol.63, no.9, 1850-1861.
Ning, B., Qu, X., Guo, D., Hu, C., Chen, Z.. Magnetic resonance image reconstruction using trained geometric directions in 2D redundant wavelets domain and non-convex optimization. Magnetic resonance imaging, vol.31, no.9, 1611-1622.
Bruckstein, A.M., Donoho, D.L., Elad, M.. From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images. SIAM review, vol.51, no.1, 34-81.
Rubinstein, R., Zibulevsky, M., Elad, M.. Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation. IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol.58, no.3, 1553-1564.
Mairal, J., Elad, M., Sapiro, G.. Sparse Representation for Color Image Restoration. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.17, no.1, 53-69.
Donoho, D.L.. Compressed sensing. IEEE transactions on information theory, vol.52, no.4, 1289-1306.
Candes, E.J., Romberg, J., Tao, T.. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE transactions on information theory, vol.52, no.2, 489-509.
Baraniuk, Richard G., Candes, Emmanuel, Elad, Michael, Ma, Yi. Applications of Sparse Representation and Compressive Sensing [Scanning the Issue]. Proceedings of the IEEE, vol.98, no.6, 906-909.
Ge Wang, Bresler, Yoram, Ntziachristos, Vasilis. Guest Editorial Compressive Sensing for Biomedical Imaging. IEEE transactions on medical imaging, vol.30, no.5, 1013-1016.
Lustig, Michael, Donoho, David, Pauly, John M.. Sparse MRI: The application of compressed sensing for rapid MR imaging. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine, vol.58, no.6, 1182-1195.
Lustig, M., Donoho, D.L., Santos, J.M., Pauly, J.M.. Compressed Sensing MRI [A look at how CS can improve on current imaging techniques]. IEEE signal processing magazine, vol.25, no.2, 72-82.
Yue Huang, Paisley, John, Qin Lin, Xinghao Ding, Xueyang Fu, Xiao-Ping Zhang. Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.23, no.12, 5007-5019.
510k Premarket Notification of HyperSense (GE Medical Systems) 2017
Chen, Shuhang, Liu, Huafeng, Shi, Pengcheng, Chen, Yunmei. Sparse representation and dictionary learning penalized image reconstruction for positron emission tomography. Physics in medicine & biology, vol.60, no.2, 807-823.
510k Premarket Notification of Compressed Sensing Cardiac Cine (Siemens) 2017
510k Premarket Notification of Compressed SENSE 2018
Tan, Shengqi, Zhang, Yanbo, Wang, Ge, Mou, Xuanqin, Cao, Guohua, Wu, Zhifang, Yu, Hengyong. Tensor-based dictionary learning for dynamic tomographic reconstruction. Physics in medicine & biology, vol.60, no.7, 2803-2818.
Wang, Yanhua, Ying, Leslie. Compressed Sensing Dynamic Cardiac Cine MRI Using Learned Spatiotemporal Dictionary. IEEE transactions on bio-medical engineering, vol.61, no.4, 1109-1120.
Caballero, Jose, Price, Anthony N., Rueckert, Daniel, Hajnal, Joseph V.. Dictionary Learning and Time Sparsity for Dynamic MR Data Reconstruction. IEEE transactions on medical imaging, vol.33, no.4, 979-994.
Zhang, Yanbo, Mou, Xuanqin, Wang, Ge, Yu, Hengyong. Tensor-Based Dictionary Learning for Spectral CT Reconstruction. IEEE transactions on medical imaging, vol.36, no.1, 142-154.
Ravishankar, Saiprasad, Nadakuditi, Raj Rao, Fessler, Jeffrey A.. Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems. IEEE transactions on computational imaging, vol.3, no.4, 694-709.
Ravishankar, Saiprasad, Moore, Brian E., Nadakuditi, Raj Rao, Fessler, Jeffrey A.. Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging. IEEE transactions on medical imaging, vol.36, no.5, 1116-1128.
Garcia-Cardona, Cristina, Wohlberg, Brendt. Convolutional Dictionary Learning: A Comparative Review and New Algorithms. IEEE transactions on computational imaging, vol.4, no.3, 366-381.
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