| A hierarchical local region-based sparse shape composition for liver segmentation in CT scans C Shi, Y Cheng, F Liu, Y Wang, J Bai, S Tamura Pattern Recognition 50, 88-106, 2015 | 84 | 2015 |
| SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography J Wang, P Lv, H Wang, C Shi Computer Methods and Programs in Biomedicine 208, 106268, 2021 | 81 | 2021 |
| Low-Rank and Sparse Decomposition Based Shape Model and Probabilistic Atlas for Automatic Pathological Organ Segmentation C Shi, Y Cheng, J Wang, Y Wang, K Mori, S Tamura Medical Image Analysis 38, 30–49, 2017 | 79 | 2017 |
| Automatic construction of statistical shape models using deformable simplex meshes with vector field convolution energy J Wang, C Shi Biomedical engineering online 16, 1-19, 2017 | 22 | 2017 |
| Multi-slice low-rank tensor decomposition based multi-atlas segmentation: Application to automatic pathological liver CT segmentation C Shi, M Xian, X Zhou, H Wang, HD Cheng Medical image analysis 73, 102152, 2021 | 11 | 2021 |
| SERR-U-Net: squeeze-and-excitation residual and recurrent block-based U-Net for automatic vessel segmentation in retinal image J Wang, X Li, P Lv, C Shi Computational and Mathematical Methods in Medicine 2021, 2021 | 9 | 2021 |
| MAD-UNet: multi-scale attention and deep supervision-based 3D UNet for automatic liver segmentation from CT J Wang, X Zhang, H Wang | 6 | 2022 |
| Deep supervision and atrous inception-based U-Net combining CRF for automatic liver segmentation from CT P Lv, J Wang, X Zhang, C Shi Scientific Reports 12 (1), 16995, 2022 | 5 | 2022 |
| Sparse Representation-Based Deformation Model for Atlas-Based Segmentation of Liver CT Images C Shi, J Wang, Y Cheng 8th International Conference on Image and Graphics, ICIG 2015, Tianjin …, 2015 | 3 | 2015 |
| Greedy algorithm based deformable simplex meshes using gradient vector flow as external energy C Shi, C Guo, Y Cheng, J Wang 7th International Conference on Biomedical Engineering and Informatics, BMEI …, 2014 | 3 | 2014 |
| Bend-Net: bending loss regularized multitask learning network for nuclei segmentation in histopathology images H Wang, A Vakanski, C Shi, M Xian arXiv preprint arXiv:2109.15283, 2021 | 2 | 2021 |
| 2.5 D cascaded context-based network for liver and tumor segmentation from CT images R Bi, L Guo, B Yang, J Wang, C Shi Electronic Research Archive 31 (8), 4324-4345, 2023 | 1 | 2023 |
| A two-stage high-dimensional feature selection method for pulmonary tumor classification in ct J Wang, C Zhao, C Shi, S Tamura, N Tomiyama Journal of Medical Imaging and Health Informatics 9 (7), 1516-1523, 2019 | 1 | 2019 |
| DA-UNet: Deep Supervision and Atrous Inception-based U-Net Combining CRF for Automatic Liver Segmentation from CT P Lv, J Wang, X Zhang, C Shi | | 2022 |
| Vector Field Convolution-Based B-Spline Deformation Model for 3D Segmentation of Cartilage in MRI J Wang, C Shi, Y Cheng, X Zhou, S Tamura Symmetry 10 (11), 591, 2018 | | 2018 |
