| PWLS-ULTRA: An efficient clustering and learning-based approach for low-dose 3D CT image reconstruction X Zheng, S Ravishankar, Y Long, JA Fessler IEEE transactions on medical imaging 37 (6), 1498-1510, 2018 | 105 | 2018 |
| BCD-Net for low-dose CT reconstruction: Acceleration, convergence, and generalization IY Chun, X Zheng, Y Long, JA Fessler Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 37 | 2019 |
| Low dose CT image reconstruction with learned sparsifying transform X Zheng, Z Lu, S Ravishankar, Y Long, JA Fessler Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2016 …, 2016 | 33 | 2016 |
| Sparse-View X-Ray CT Reconstruction Using l1 Regularization with Learned Sparsifying Transform IY Chun, X Zheng, Y Long, JA Fessler The 14th International Meeting on Fully Three-Dimensional Image …, 2017 | 24 | 2017 |
| Sparse-View X-Ray CT Reconstruction Using l1 Prior with Learned Transform X Zheng, IY Chun, Z Li, Y Long, JA Fessler arXiv preprint arXiv:1711.00905, 2019 | 17 | 2019 |
| Union of Learned Sparsifying Transforms Based Low-Dose 3D CT Image Reconstruction X Zheng, S Ravishankar, Y Long, JA Fessler The 14th International Meeting on Fully Three‐Dimensional Image …, 2017 | 12 | 2017 |
| Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging IY Chun, D Park, X Zheng, SY Chun, Y Long arXiv preprint arXiv:2205.04821, 2022 | 1 | 2022 |
| Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction X Yang, X Zheng, Y Long, S Ravishankar The 6th International Conference on Image Formation in X-Ray Computed …, 2021 | 1 | 2021 |
| Two-Layer Residual Sparsifying Transform Learning for Image Reconstruction X Zheng, S Ravishankar, Y Long, ML Klasky, B Wohlberg 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 174-177, 2020 | 1 | 2020 |
Jeff FesslerProfessor of Electrical Engineering and Computer Science, Univ. of MichiganVerified email at umich.edu
