2022:
1. Y Du, Q Quan, H Han, and S Kevin Zhou. Semi-supervised pseudo-healthy image synthesis via confidence augmentation. IEEE International Symposium on Biomedical Imaging (ISBI), 2022.
2. L Yang, H Han, and S Kevin Zhou. Deep nonlinear embedding deformation network for cross-modal brain MRI synthesis. IEEE International Symposium on Biomedical Imaging (ISBI), 2022.
3. X Liu, J Wang, C Peng, S Chandra, F Liu, and S Kevin Zhou. Undersampled MRI reconstruction with side information guided normalization. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022.
4. Z Zhao, F Zhou, Z Zeng, C Guan, and S Kevin Zhou. Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022.
5. J Zhu, Y Li, L Ding, and S Kevin Zhou. Aggregative self-supervised feature learning from limited medical sample. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022.
6. C Peng, P Guo, S Kevin Zhou, V Patel, and R Chellappa. Towards performant and reliable undersampled MR reconstruction via diffusion model sampling. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022. (oral)
7. R Liu, Q Ma, Z Cheng, Y Lyu, J Wang, and S Kevin Zhou. Stabilize, decompose, and denoise: Selfsupervised fluoroscopy denoising. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022.
8. X Wu, S Yang, Z Qiu, S Ge, Y Yan, X Wu, Y Zheng, S Kevin Zhou, L Xiao. DeltaNet: Conditional medical report generation for COVID-19 diagnosis. International Conference on Computational Linguistics, 2022.
9. J Wei, S Wang, Z Li, S Kevin Zhou, and S Cui. Weakly supervised object localization through interclass feature similarity and intra-class appearance consistency. European Conference on Computer Vision (ECCV), 2022.
10. B Zhou, X Chen, S Kevin Zhou, JS Duncan, and C Liu. DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography. Medical Image Analysis, 75:102289, January 2022. (PMID: 34758443, DOI: 10.1016/j.media.2021.102289)
11. F Yang, J Zhu, J Wang, L Zhang, W Wang, X. Chen, X Lin, Q Wang, D Burkhoff, S Kevin Zhou, and K. He. Self-supervised learning assisted diagnosis for mitral regurgitation severity classification based on color Doppler echocardiography. Annals of Translational Medicine, Vol. 10 No. 1, January 2022.
12. L Han, Y Lyu, C Peng, and S Kevin Zhou. GAN-based disentanglement learning for chest X-ray rib suppression. Medical Image Analysis, 77:102369, April 2022, 102369. (DOI: 10.1016/j.media.2022.102369)
13. H Zhu, Q Yao, L Xiao, and S Kevin Zhou. Learning to localize cross-anatomy landmarks in X-ray images with a universal model. BME Frontiers, 2022.
14. S Yang, X Wu, S Ge, S Kevin Zhou, and L Xiao. Knowledge matters: Chest radiology report generation with general and specific knowledge. Medical Image Analysis, 80:102510, August 2022.
15. B Zhou, X Chen, H Xie, S Kevin Zhou, JS Duncan, and C Liu. DuDoUFNet: Dual-domain under-tofully-complete progressive restoration network for simultaneous metal artifact reduction and low-dose CT reconstruction. IEEE Trans. on Medical Imaging, 2022.
16. B Zhou, T Miao, et al. S Kevin Zhou, JS Duncan, and C Liu. Federated transfer learning for low-dose PET denoising: A pilot Study with simulated heterogeneous data. IEEE Trans. on Radiation and Plasma Medical Sciences, 2022.
17. Z Zhao, F Zhou, K Xu, Z Zeng, C Guan, and S Kevin Zhou. LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation. IEEE Trans. on Medical Imaging, 2022. (accepted)
18. Han Li, Long Chen, Hu Han, and S. Kevin Zhou. SATr: Slice Attention with Transformer for Universal Lesion Detection. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 163-174, Singapore, Sept. 18-22, 2022.
19. Zhu, Heqin, Qingsong Yao, Li Xiao, and S. Kevin Zhou. “Learning to Localize Cross-Anatomy Landmarks in X-Ray Images with a Universal Model.” BME Frontiers 2022 (2022).
20. Sun, Yihua, Qingsong Yao, Yuanyuan Lyu, Jianji Wang, Yi Xiao, Hongen Liao, and S. Kevin Zhou. “Rib Suppression in Digital Chest Tomosynthesis.” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 696–706, Singapore, Sept. 18-22, 2022.
21. Pengbo Liu, et. al. and S. Kevin Zhou. Learning Incrementally to Segment Multiple Organs in a CT Image. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 714-724, Singapore, Sept. 18-22, 2022.
22. Han Li, Long Chen, Hu Han, and S. Kevin Zhou. SATr: Slice Attention with Transformer for Universal Lesion Detection. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 163-174, Singapore, Sept. 18-22, 2022.
23. Jun Wei, Yiwen Hu, Guanbin Li, Shuguang Cui, S Kevin Zhou, Zhen Li. BoxPolyp: Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations. International Conference on Medical Image Computing and Computer Assisted Intervention(MICCAI), pp. 67-77, Singapore, Sept. 18-22, 2022
24. Jun Wei, Sheng Wang, S Kevin Zhou, Shuguang Cui, Zhen Li. Weakly supervised object localization through inter-class feature similarity and intra-class appearance consistency. European Conference on Computer Vision(ECCV), pp. 195-210, Tel Aviv, Oct. 25-27, 2022
25. L. Han, Y. Lyu, C. Peng, and S. Kevin. Zhou, “Gan-based disentanglement learning for chest x-ray rib suppression,” Medical Image Analysis, 2022: 102369.
2021:
1. S. Kevin. Zhou, H. N. Le, K. Luu, H. V. Nguyen, and N. Ayache, “Deep reinforcement learning in medical imaging: A literature review,” Medical Image Analysis, 2021: 102193.
2. B. Zhou, X. Chen, S. Kevin Zhou, et al., “DuDoDR-Net: Dual-Domain Data Consistent Recurrent Network for Simultaneous Sparse View and Metal Artifact Reduction in Computed Tomography”, Medical Image Analysis, 2021: 102289.
3. P. Cheng, S. Kevin Zhou, and R. Chellappa, “DA-VSR: Domain adaptable volumetric super-resolution for medical images,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
4. M. Guan, Y. Lyu, W. Cao, X. Wu, J. Lu, and S. Kevin Zhou, “Perceptual quality assessment of chest radiograph,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
5. Y. Lyu, J. Fu, C. Peng, and S. Kevin Zhou, “U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
6. J. Wei, Y. Hu, R. Zhang, Z. Li, S. Kevin Zhou, and S. Cui, “Shallow attention network for enhanced small polyp segmentation,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
7. X. Liu, J. Wang, F. Liu, and S. Kevin Zhou, “Universal undersampled MRI reconstruction,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
8. C. Wang, H. Zhang, Q. Li, K. Shang, Y. Lyu, B. Dong, and S. Kevin Zhou, “Generalizable limited-angle CT reconstruction via sinogram extrapolation,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
9. H. Zhu, Q. Yao, L. Xiao, and S. Kevin Zhou, “You only learn once: Universal anatomical landmark detection,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
10. H. Li, L. Chen, H. Han, and S. Kevin Zhou, “Conditional training with bounding map for universal lesion detection,”International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
11. Q. Yao, Q. Quan, L. Xiao, and S. Kevin Zhou, “One-shot medical landmark detection,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September 2021.
12. Q. Yao, Z. He, Y. Lin, K. Ma, Y. Zheng, and S. Kevin Zhou, “Hierarchical feature constraint to camouflage medical adversarial attacks,”International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Strasbourg, France, September
13. J. Wei, Q. Wang, Z. Li, S. Wang, S. Kevin Zhou, and S. Cui, “Shallow feature matters for weakly supervised object localization,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2021. （accepted）
14. H. Lu, H. Han, and S. Kevin Zhou, “Dual-GAN: Joint BVP and noise modeling for remote physiological measurement,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (accepted)
15. X. Wei, Z. Yang, X. Zhang, G. Liao, A. Sheng, S. Kevin Zhou, Y. Wu, L. Du, “Deep collocative learning for immunofixation electrophoresis image analysis,” IEEE Trans. on Medical Imaging, 2021, 40 (7), 1898-1910
16. Bo Zhou, Zachary Augenfeld, Julius Chapiro, S. Kevin Zhou, Chi Liu, and J. S. Duncan, “Anatomyguided multimodal registration by learning segmentation without ground truth: Application to intraprocedural CBCT/MR liver segmentation and registration,” Medical Image Analysis, 2021. (accepted)
17. B. Zhou, S. Kevin Zhou, J.S. Duncan, and C. Liu, “Limited view tomographic reconstruction using a cascaded residual dense spatial-channel attention network with projection data fidelity layer”, IEEE Trans. on Medical Imaging, 2021. (accepted)
18. Jiancheng Cai, Hu Han, Jiyun Cui, Jie Chen, Li Liu, S. Kevin Zhou, "Semi-Supervised Natural Face De-Occlusion," IEEE Trans. Inf. Forensics Secur. 16: 1044-1057 (2021)
19. S. Kevin Zhou, H. Greenspan, C. Davatzikos, J.S. Duncan, B. van Ginneken, A. Madabhushi, J.L. Prince, D. Rueckert, and R.M. Summers, “A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises,” Proceedings of the IEEE, 2021.
20. W. Zhang, M. Sun, Y. Fan, H. Wang, M. Feng, S. Kevin Zhou and R. Wang, “Machine learning in preoperative prediction of postoperative immediate remission of Cushing’s disease”, Frontiers in Endocrinology, 2021.
21. Q. Yao, L. Xiao, P. Liu, and S. Kevin Zhou, “Label-free segmentation of COVID-19 lesions in lung CT,” IEEE Trans. on Medical Imaging, 2021. (accepted)
22. G. Shi, L. Xiao, Y. Chen, and S. Kevin Zhou, “Marginal loss and exclusion loss for partially supervised multi-organ segmentation,” Medical Image Analysis, 2021.
23. Y. Lyu, H. Liao, H. Zhu, and S. Kevin Zhou, “A3DSegNet: Anatomy-aware artifact disentanglement and segmentation network for unpaired segmentation, artifact reduction, and modality translation,” Information Processing in Medical Imaging (IPMI), 2021. (accepted)
24. R. Gao, Z. Hou, J. Li, H. Han, B. Lu, and S. Kevin Zhou, “Joint Coronary Centerline Extraction and Lumen Segmentation from CCTA using CNNTracker and Vascular Graph Convolutional Network,” IEEE International Symposium on Biomedical Imaging (ISBI), 2021. (accepted)
25. P. Liu, et al. S. Kevin Zhou, “Deep learning to segment pelvic bones: large-scale CT datasets and baseline models,” Information Processing in Computer-Assisted Interventions (IPCAI), 2021. (accepted)
26. R. Gao, Y. Gao, H. Han, S. Kevin Zhou, and Bin Lu, “Cardiac event prediction by evaluating variation of perivascular adipose tissue in serial coronary CT angiography,” European Congress of Radiology (ECR), 2021. (accepted)
27. P. Cheng, H. Liao, G. Wong, J. Luo, S. Kevin Zhou and R. Chellappa, “XraySyn: Realistic view synthesis from a single radiograph through CT priors,” The 35th AAAI Conference on Artificial Intelligence, February 2021. (accepted)
2020:
1. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part I," Lecture Notes in Computer Science 12261, Springer 2020, ISBN 978-3-030-59709-2
2. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II," Lecture Notes in Computer Science 12262, Springer 2020, ISBN 978-3-030-59712-2
3. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part III," Lecture Notes in Computer Science 12263, Springer 2020, ISBN 978-3-030-59715-3
4. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV," Lecture Notes in Computer Science 12264, Springer 2020, ISBN 978-3-030-59718-4
5. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part V," Lecture Notes in Computer Science 12265, Springer 2020, ISBN 978-3-030-59721-4
6. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VI," Lecture Notes in Computer Science 12266, Springer 2020, ISBN 978-3-030-59724-5
7. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, "Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VII," Lecture Notes in Computer Science 12267, Springer 2020, ISBN 978-3-030-59727-6
8. C. Peng, W. Lin, R. Chellappa, and S. Kevin Zhou, “Towards multi-sequence MR image recovery from undersampled k-space data,” in Medical Imaging with Deep Learning, pp. 614-623, PMLR, 2020. (oral, 12% acceptance)
9. Z. Shen, Y. Chen, S. Kevin Zhou, B. Georgescu, X. Liu and T.S. Huang, “Learning a self-inverse network for bidirectional MRI image synthesis,” in IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1765-1769, 2020.
10. Q. Yao, Z. He, H. Han, and S. Kevin Zhou, “Miss the point: Targeted adversarial attack on multiple landmark detection,” in MICCAI, pp. 692-702, Springer, 2020.
11. H. Li, H. Han, and S. Kevin Zhou: "Bounding maps for universal lesion detection," in MICCAI, pp. 417-428, Springer, 2020.
12. Z. Huang, Y. Ding, G. Song, L. Wang, R. Geng, H. He, S. Du, X. Liu, Y. Tian, Y. Liang, S. Kevin Zhou, and J. Chen, "BCData: A large-scale dataset and benchmark for cell detection and counting," in MICCAI, pp. 289-298, Springer, 2020.
13. Y. Lyu, W. Lin, H. Liao, J. Lu, and S. Kevin Zhou, "Encoding metal mask projection for metal artifact reduction in computed tomography," in MICCAI, pp. 147-157, Springer, 2020.
14. W. Wang, Q. Song, J. Zhou, R. Feng, T. Chen, W. Ge, D.Z. Chen, S. Kevin Zhou, W. Wang, and J. Wu, "Dual-level selective transfer learning for intrahepatic cholangiocarcinoma segmentation in non-enhanced abdominal ct," in MICCAI, pp. 64-73, Springer, 2020.
15. J. Zhu, Y. Li, Y. Hu, K. Ma, S. Kevin Zhou, Y. Zheng: "Rubik’s Cube+: A Self-supervised Feature Learning Framework for 3D Medical Image Analysis," Medical Image Analysis, vol. 64, p. 101746, 2020.
16. H. Li, H. Han, Z. Li, L. Wang, Z. Wu, J. Lu, and S. Kevin Zhou, "High-Resolution Chest X-ray Bone Suppression Using Unpaired CT Structural Priors," IEEE transactions on medical imaging, vol. 39, no. 10, pp. 3053-3063, 2020.
Note: The Laplacian of Gaussian (LoG) operator is designed according to the LoG definition [code]. We did not subtract its mean value to make its sum equal to 0, which is done by open-cv library function in python.
17. C. Peng, W.-A. Lin, H. Liao, R. Chellappa, S. Kevin Zhou, "SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis," in IEEE CVPR, pp. 7747-7756, 2020.
18. B. Zhou, S. Kevin Zhou, "DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior," IEEE CVPR, pp. 4272-4281, 2020.
19. Z. Shen, S. Kevin Zhou, Y. Chen, B. Georgescu, X. Liu, and T.S. Huang, "One-to-one mapping for unpaired image-to-image translation," IEEE WACV, 1159-1168, 2020.
20. H. Liao, W.A. Lin, S. Kevin Zhou and J. Luo, "ADN: Artifact disentanglement network for unsupervised metal artifact reduction," IEEE Trans. on Medical Imaging, Vol. 39, No. 3, pp. 634-643, 2020. (PMID: 31395543)
2019:
1. S. Kevin Zhou, Daniel Rueckert, and Gabor Fichtinger (Eds.), Handbook of Medical Image Computing and Computer Assisted Intervention. Academic Press, 2019. MICCAI book series. (in press)
ISBN: 9780128161760
2. S. Kevin Zhou and Z. Xu, Landmark detection and multi-organ segmentation: Representations and supervised approaches. Handbook of Medical Image Computing and Computer Assisted Intervention, S. Kevin Zhou, D. Rueckert, and G. Fichtinger (Eds.), Academic Press, 2019.
3. D. Yang, T. Xiong, D. Xu and S. Kevin Zhou, Segmentation using adversarial image-to-image networks. Handbook of Medical Image Computing and Computer Assisted Intervention, S. Kevin Zhou, D. Rueckert, and G. Fichtinger (Eds.), Academic Press, 2019.
4. S. Taghanaki, Y. Zheng, S. Kevin Zhou, et al. and Ghassan Hamarneh, “Combo loss: Handling input and output imbalance in multi-organ segmentation,” Comp. Med. Imag. and Graph., Vol. 75, pp. 24-33, 2019.
5. Zeju Li, Han Li, Hu Han, Gonglei Shi, Jiannan Wang, S. Kevin Zhou. Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition. MICCAI 2019.
6. Chao Huang, Hu Han, Qingsong Yao, Shankuan Zhu, S. Kevin Zhou. 3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation. MICCAI 2019.
7. Haofu Liao, Wei-An Lin, Zhimin Huo, Levon Vogelsang, William J. Sehnert, S. Kevin Zhou, Jiebo Luo. Generative Mask Pyramid Network forCT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction. MICCAI 2019.
8. Haofu Liao, Wei-An Lin, Jianbo Yuan, S. Kevin Zhou, Jiebo Luo. Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction. MICCAI 2019.
9. Haofu Liao, Wei-An Lin, Jiarui Zhang, Jingdan Zhang, Jiebo Luo, S. Kevin Zhou: Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation. CVPR 2019: 12638-12647.
10. Wei-An Lin, Haofu Liao, Cheng Peng, Xiaohang Sunm, Jingdan Zhang, Jiebo Luo, Rama Chellappa, Shaohua Kevin Zhou: DuDoNet: Dual Domain Network for CT Metal Artifact Reduction. CVPR 2019: 10512-10521.
2018:
1. Hui Ding, Hao Zhou, Shaohua Kevin Zhou, Rama Chellappa: A Deep Cascade Network for Unaligned Face AttributeClassification. AAAI 2018: 6789-6796
2. Haofu Liao, Zhimin Huo, William J. Sehnert, Shaohua Kevin Zhou, Jiebo Luo: Adversarial Sparse-View CBCT Artifact Reduction. MICCAI (1) 2018: 154-162
3. Haofu Liao, Yucheng Tang, Gareth Funka-Lea, Jiebo Luo, Shaohua Kevin Zhou:More Knowledge Is Better: Cross-Modality Volume Completion and 3D+2D Segmentation for Intracardiac Echocardiography Contouring. MICCAI (2) 2018: 535-543
4. Zhoubing Xu, Yuankai Huo, Jin Hyeong Park, Bennett A. Landman, Andy Milkowski, Sasa Grbic, Shaohua Kevin Zhou: Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images. MICCAI (2) 2018: 711-719
5. Siqi Liu, Daguang Xu, Shaohua Kevin Zhou, Olivier Pauly, Sasa Grbic, Thomas Mertelmeier, Julia Wicklein, Anna K. Jerebko, Weidong Cai, Dorin Comaniciu:3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes. MICCAI (2) 2018: 851-858
6. Qiangui Huang, Shaohua Kevin Zhou, Suya You, Ulrich Neumann: Learning to Prune Filters in Convolutional Neural Networks. WACV 2018: 709-718
7. H. Liao, Y. Zheng, G. Funka-lea, J. Luo, S. Kevin Zhou, “Face completion with semantic knowledge and collaborative adversarial learning,” Asian Conference on Computer Vision (ACCV), Perth, Australia, December 2018.
2017:
1. Hui Ding, Shaohua Kevin Zhou, Rama Chellappa:FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition. FG 2017: 118-126
2. Dong Yang, Tao Xiong, Daguang Xu, Qiangui Huang, David Liu, Shaohua Kevin Zhou, Zhoubing Xu, Jin Hyeong Park, Mingqing Chen, Trac D. Tran, Sang Peter Chin, Dimitris N. Metaxas, Dorin Comaniciu: Automatic Vertebra Labeling in Large-Scale 3D CT Using Deep Image-to-Image Network with Message Passing and Sparsity Regularization. IPMI 2017: 633-644
3. Zhoubing Xu, Qiangui Huang, Jin Hyeong Park, Mingqing Chen, Daguang Xu, Dong Yang, David Liu, Shaohua Kevin Zhou: Supervised Action Classifier: Approaching Landmark Detection as Image Partitioning. MICCAI (3) 2017: 338-346
4. Dong Yang, Tao Xiong, Daguang Xu, Shaohua Kevin Zhou, Zhoubing Xu, Mingqing Chen, Jin Hyeong Park, Sasa Grbic, Trac D. Tran, Sang Peter Chin, Dimitris N. Metaxas, Dorin Comaniciu: Deep Image-to-Image Recurrent Network with Shape Basis Learning for Automatic Vertebra Labeling in Large-Scale 3D CT Volumes. MICCAI (3) 2017: 498-506
5. Dong Yang, Daguang Xu, Shaohua Kevin Zhou, Bogdan Georgescu, Mingqing Chen, Sasa Grbic, Dimitris N. Metaxas, Dorin Comaniciu: Automatic Liver Segmentation Using an Adversarial Image-to-Image Network. MICCAI (3) 2017: 507-515
6. Raviteja Vemulapalli, Hien Van Nguyen, Shaohua Kevin Zhou: Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis. Deep Learning for Medical Image Analysis 2017: 381-403
7. Shaohua Kevin Zhou, Hayit Greenspan, Dinggang Shen: Deep Learning for Medical Image Analysis, 1st Edition. Academic Press 2017, ISBN 978-0-12-810408-8 [contents]
