2025:
[1] Y Sang, et al. Benchmark of segmentation techniques for pelvic fracture in CT and X-ray: Summary of the PENGWIN 2024 challenge. IEEE Transactions on Medical Imaging, 2025.
[2] Y Jiang, C-M Feng, J Ren, J Wei, Z Zhang, Y Hu, Y Liu, R Sun, X Tang, J Du, X Wan, Y Xu, B Du, X Gao, G Wang, S Kevin Zhou, S Cui, RSM Goh, Y Liu, Z Li. From pretraining to privacy: Federated ultrasound foundation model with self-supervised learning. npj Digital Medicine, 2025.
[3] H Lai, Z Jiang, Q Yao, R Wang, Z He, X Tao, W Wei, W Lv, and S Kevin Zhou. Bridged semantic alignment for zero-shot 3D medical image diagnosis. Journal of Biomedical and Health Informatics, 2025.
[4] X Zhang, M Zhao, F Yao, W Ma, J Zhang, Y Li, X Zhou, Y Guan, Y Xiao, L Fan, and S Kevin Zhou, S Liu. Self-supervised anomaly detection and staging for CT emphysema. Patterns, 2025.
[5] F Tang, Q Yao, W Ma, C Wu, Z Jiang, and S Kevin Zhou. Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation. Medical Image Analysis, 103770, 2025.
[6] R Yan, X Zhang, Z Jiang, B Wang, X Bian, F Ren, and S Kevin Zhou. Pathway-aware multimodal transformer (PAMT): Integrating pathological image and gene expression for interpretable cancer survival analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2025.
[7] B Nian, F Tang, J Ding, P Zhang, J Yang, S Kevin Zhou, W Liu. SRS: Siamese reconstruction-segmentation network based on dynamic-parameter convolution. IEEE Transactions on Image Processing, 2025.
[8] L Han, T Tan, Y Huang, H Dou, T Zhang, Y Gao, X Wang, C Lu, X Liang, Y Sun, J Teuwen, S Kevin Zhou, R Mann. All in one medical image-to-image translation. Cell Reports Methods, 101138, 2025.
[9] J Dong, Y Zhang, Q Wang, R Tong, S Ying, S Gong, X Zhang, L Lin, Y Chen, and S Kevin Zhou. Deep self-cleansing for medical image segmentation with noisy labels. Medical Physics, 2025.
[10] M Zhao, H Li, D Zhang, J Zhang, X Zhou, L Fan, X Qiu, S Liu, and S Kevin Zhou. Skeleton2Mask: Skeleton-supervised airway segmentation. Medical Image Analysis, 103693, 2025.
[11] D Zhang, M Zhao, X Zhou, Y Li, Y Guan, Y Xia, J Zhang, Q Dai, J Zhang, L Fan, S Kevin Zhou, S Liu. Single inspiratory chest CT based generative deep learning models to evaluate functional small airway disease. Radiology: Artificial Intelligence, 2025.
[12] Y Wang, Y Gu, X Zhang, B Wang, R Wang, Y Liu, X Li, F Qu, F Ren, R Yan, and S Kevin Zhou. A review of computational pathology in precision oncology: Evolution from task-specific models to foundation models. Chinese Medical Journal, 2025.
[13] H Luan, T Hu, et al. R Yan, S Kevin Zhou, B Niu. Breast cancer homologous recombination deficiency prediction from pathological images with a sufficient and representative Transformer. npj Precision Oncology, 2025.
[14] R Wang, Q Yao, Z Jiang, H Lai, Z He, X Tao and S Kevin Zhou. ECAMP: Entity-centered context-aware medical vision language pre-training. Medical Image Analysis, 103690, 2025.
[15] Y Deng, Z Ji, Y Wang, and S Kevin Zhou. CCA-Net: Zero-shot SSVEP classification via an integration of canonical correlation analysis and deep neural network. IEEE Trans. on Instrumentation & Measurement, 2025.
[16] Z Xu, F Tang, Q Quan, Q Yao, Q Kong, J Ding, C Ning, and S Kevin Zhou. Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings. npj Digital Medicine, 8(1):1-9, 2025.
[17] F Tang, B Nian, Y Li, J Yang, L Wei and S Kevin Zhou. MambaMIM: Pre-training Mamba with state space token-interpolation and its application to medical image segmentation. Medical Image Analysis, 103606, 2025.
[18] Y Li, X Fu, H Li, S Zhao, R Jing and S Kevin Zhou. 3DGR-CT: Sparse-view CT reconstruction with a 3D Gaussian representation. Medical Image Analysis, 103585, 2025.
[19] H Zhu, F Tang, Q Quan, K Chen, P Xiong, and S Kevin Zhou. Deep generalizable prediction of RNA secondary structure via base pair motif energy. Nature Communications, 2025.
[20] J Wang, et al. BMJ Innovations Roundtable: Innovations that will have the biggest impact on orthopaedics over the next decade. BMJ Innovations, 2025.
[21] K Lekadir, et al. FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. British Medical Journal, 2025.
[22] C Wang, R Yan, K Zhang, Z Jiang, Z He, X Tao, and S Kevin Zhou. KANTrust: A multi-omics framework for uncertainty-aware disease subtyping. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Wuhan, China, 2025.
[23] X Li, W Ye, and S Kevin Zhou. Distilling dataset summarization via constrained diffusion model for shareable synthetic histopathology image. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , Wuhan, China, 2025.
[24] Y Feng, J Lv, Y Cao, X Xie, S Kevin Zhou. Ada-KV: Optimizing KV cache eviction by adaptive budget allocation for efficient LLM inference. NeurIPS, 2025.
[25] H Wang, Y Feng, Y Cao, X Xie, and S Kevin Zhou. SkewRoute: Training-free LLM routing for knowledge graph retrieval-augmented generation via score skewness of retrieved context. EMNLP Findings, Suzhou, China, 2025.
[26] S Zhuo, Z Gao, Y Zhang, K Li, and S Kevin Zhou. Deep learning for high-resolution reconstruction of dynamic OCT. SPIE/COS Photonics Asia, Beijing, 2025.
[27] C Dong, F Tang, R Mao, X Gao and S Kevin Zhou. LGMSNet: Thinning a medical image segmentation model via dual-level multiscale fusion. European Conference on Artificial Intelligence (ECAI), 2025.
[28] F Tang, B Nian, J Ding, W Ma, Q Quan, C Dong, J Yang, W Liu, and S Kevin Zhou. Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation. ACM Multimedia (ACMMM), Dublin, Ireland, 2025.
[29] P Zhao, H Li, R Jin, and S Kevin Zhou. LoCo: Training-free layout-to-image synthesis with localized constraints. ACM Multimedia (ACMMM), Dublin, Ireland, 2025.
[30] Y Li, H Lai, X Zhou, S Ming, W Ma, W Wei, and S Kevin Zhou. More performant and scalable: Rethinking contrastive vision-language pre-training of radiology in the LLM era. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[31] H Ye, P Zhao, F Tang, D Zhao, Z Huang, M Bian, and S Kevin Zhou. U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKV. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[32] S Chen, Z Huang, X Zhou, H Li, C Wang, and S Kevin Zhou. PATE: Enhancing few-shot pathological image classification via prompt-based text-image embedding adaptation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[33] X Fu, P Wu, Y Li, X Luo, Z Jiang, J Mei, J Lu, G Teng, and S Kevin Zhou. Dyna3DGR: 4D cardiac motion tracking with dynamic 3D Gaussian representation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[34] A Shen, X Fu, J Jiang, Q Zeng, Y Tang, Z Chen, L Nong, F Wang, and S Kevin Zhou. RadGS-Reg: Registering spine CT with biplanar X-rays via joint 3D radiative Gaussians reconstruction and 3D/3D registration. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[35] Z Xu, H Li, D Sun, Z Li, Y Li, Q Kong, Z Cheng, N Navab, and S Kevin Zhou. NeRF-based CBCT reconstruction needs normalization and initialization. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[36] R Wang, F Tang, Q Yao, R Yan, X Zhang, Z Huang, Z He, X Tao, Z Jiang, and S Kevin Zhou. SimCroP: Radiograph representation learning with similarity-driven cross-granularity pre-training. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[37] F Tang, W Ma, Z He, X Tao, Z Jiang, and S Kevin Zhou. Pre-trained LLM is a semantic-aware and generalizable segmentation booster. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Daejeon, Korea, 2025.
[38] Y Cao, Z Gao, Z Li, X Xie, S Kevin Zhou, and J Xu. LEGO-GraphRAG: Modularizing graph-based retrieval-augmented generation for design space exploration. International Conference on Very Large Data Bases (VLDB), 2025.
[39] Q Wang, Y Liu, S Zhao, R Liu, and S Kevin Zhou. Label-supervised surgical instrument segmentation using temporal equivariance and semantic continuity. International Conference on Intelligent Robots and Systems (IROS), Hangzhou, China, 2025.
[40] Y Cao, S Han, Z Gao, Z Ding, X Xie and S Kevin Zhou. GraphInsight: Unlocking insights in large language models for graph structure understanding. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), Vienna, Austria, 2025.
[41] Z Gao, Y Cao, H Wang, A Ke, Y Feng, S Kevin Zhou, and X Xie. FRAG: A flexible modular framework for retrieval-augmented generation based on knowledge graphs. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL) Findings, Vienna, Austria, 2025.
[42] X Zhang, K Zhang, W Ma, R Wang, C Wu, Y Li, and S Kevin Zhou. A general knowledge injection framework for ICD coding. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL) Findings, Vienna, Austria, 2025.
[43] X He, Z Huang X Zhou, and S Kevin Zhou. Eliminating ambiguities in one-shot medical landmark detection via mask drawing. International Conference on Intelligent Computing (ICIC), Ningbo, China, 2025.
[44] H Chen, Z Huang, X Zhou, and S Kevin Zhou. A unified framework for few-shot medical image classification via multi-agent description generation and refined contrastive learning. International Conference on Intelligent Computing (ICIC), Ningbo, China, 2025.
[45] G Ding, Z Huang, and S Kevin Zhou. RMB is vital: Using a residual Mamba block in skip-connection of U-shape networks for improved segmentation. International Conference on Intelligent Computing (ICIC), Ningbo, China, 2025.
[46] J Wu and S Kevin Zhou. Cross-modal adaptation of medical vision-language model for few-shot classification. International Conference on Intelligent Computing (ICIC), Ningbo, China, 2025.
[47] Y Feng, Y Cao, H Wang, X Xie, and S Kevin Zhou. Lego Sketch: A scalable memory-augmented neural network for sketching data streams. International Conference on Machine Learning (ICML), Vancouver, Canada, 2025.
[48] C Wang, K Zhang, Y Liu, Z He, X Tao, and S Kevin Zhou. MVP-CBM: Multi-layer visual preferenceenhanced concept bottleneck model for explainable medical image classification. The 34th International Joint Conference on Artificial Intelligence (IJCAI-25), Montreal, Canada, 2025.
[49] A Ke, W Chen, C Feng, Y Cao, X Xie, S Kevin Zhou, and L Feng. Prototype-based optimal transport for out-of-distribution detection. The 34th International Joint Conference on Artificial Intelligence (IJCAI-25), Montreal, Canada, 2025.
[50] J Shi, X Luo, and S Kevin Zhou. Slide-CLIP: A simple and effective pruning method for CLIP. International Joint Conference on Neural Networks (IJCNN), Rome, Italy, 2025.
[51] R Jin, Q Quan, and S Kevin Zhou. Multi-phase renal tumor segmentation with Slide-SAM assisted network. Medical Imaging with Deep Learning (MIDL) Short Paper, Salt Lake City, Utah, USA 2025.
[52] Y Chang, Z Jiang, K Zhang, and S Kevin Zhou. FundusAdapter: Few-shot adaptation of fundus image foundation model for fundus image diagnosis. Medical Imaging with Deep Learning (MIDL) Short Paper, Salt Lake City, Utah, USA 2025.
[53] Y Li, S Ming, H Lai, F Tang, W Wei, and S Kevin Zhou. Scaling supervision for free: Leveraging universal segmentation models for enhanced medical image diagnosis. Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah, USA 2025.
[54] M Bian, K Zhang, D Zhao, and S Kevin Zhou. DiffRGenNet: Difference-aware medical report generation. Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah, USA 2025.
[55] W Bo, T Xue, L Pan, D Huang, Y Xiao, L Fan, Z Liu, S Liu, and S Kevin Zhou. RCSegNeXt: Efficient multi-scale ConvNeXt for rectal cancer segmentation from sagittal MRI scans. Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah, USA 2025.
[56] Q Qi, X Li, M Kong, Z Xu, B Chen, Q Zhu, and S Kevin Zhou. Style-aligned image composition for robust detection of abnormal cells in cytopathology. Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah, USA 2025.
[57] Y Li, H Li, and S Kevin Zhou. Causal PETS: Causality-informed PET synthesis from multi-modal data. Medical Imaging with Deep Learning (MIDL), Salt Lake City, Utah, USA 2025.
[58] W Ma, X Zhang, Q Yao, F Tang, C Wu, Y Li, R Yan, Z Jiang, and S Kevin Zhou. AA-CLIP: Enhancing zero-shot anomaly detection via anomaly-aware CLIP. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, USA, 2025.
[59] X Luo, X Fu, Z Jiang, and S Kevin Zhou. ICP: Immediate compensation pruning for mid-to-high sparsity. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, USA, 2025.
[60] K Zhang, J Li, Z Li, and S Kevin Zhou. DH-Set: Improving vision-language alignment with diverse and hybrid set-embeddings learning. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, USA, 2025.
[61] C Wu, Q Kong, Z Jiang, and S Kevin Zhou. Self-supervised diffusion MRI denoising via iterative and stable refinement. The International Conference on Learning Representations (ICLR), Singapore, 2025.
[62] M Zhao, X Qiu and S Kevin Zhou. ExpTopo: Explicit topological modeling for bronchus segmentation. International Symposium on Biomedical Imaging (ISBI), Houston TX, USA, 2025.
[63] F Yang and S Kevin Zhou. EDA: Enhanced domain-adversarial training for anatomical landmark detection. International Symposium on Biomedical Imaging (ISBI), Houston TX, USA, 2025.
[64] Z Gao, W Yang, Y Li, L Xing, and S Kevin Zhou. MS-Glance: Non-semantic context vectors and the applications in supervising image reconstruction. Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona, USA, 2025.
[65] W Yang, Z Jiang, S Zhao, and S Kevin Zhou. PostoMETRO: Pose token enhanced mesh transformer for robust 3D human mesh recovery. Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona, USA, 2025.
[66] W Ma, Q Yao, X Zhang, Z Huang, Z Jiang, and S Kevin Zhou. Towards accurate unified anomaly segmentation. Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona, USA, 2025.
[67] Y Xiang, Z Ding, R Guo, S Wang, X Xie, and S Kevin Zhou. Capsule: An out-of-core training mechanism for colossal GNNs. ACM SIGMOD Conference, Berlin, Germany, 2025.
2024：
1. Q Wang, SZhao, ZXu,and SKevinZhou. LACOSTE:Exploiting stereo and temporal contexts for surgical instrument segmentation. Medical Image Analysis, 2024. (accepted)
2. Y Deng, Z Ji, Y Wang, and S Kevin Zhou. OS-SSVEP: One-shot SSVEP classification. Neural Networks, 2024.
3. K Li, et al. and S Kevin Zhou. O-PRESS: Boosting OCT axial resolution with prior guidance, recurrence, and equivariant self-supervision. Medical Image Analysis, 2024.
4. S Kevin Zhou, Q Dou, Y Gao, H Han, J Ma, J Sun, D Zhang, S Zhao, and Y Zheng. Artificial intelligence algorithm advances in medical imaging and image analysis. Artificial Intelligence in Medical Imaging in China, Shiyuan Liu (Ed.), 83-110, 2024.
5. Y Zhou, T Chen, J Hou, H Xie, NC Dvornek, S Kevin Zhou, DL Wilson, JS Duncan, C Liu, and B Zhou. Cascaded multi-path shortcut diffusion model for medical image translation. Medical Image Analysis, 2024.
6. Q Quan, Q Yao, H Zhu, and S Kevin Zhou. IGU-Aug: Information-guided unsupervised augmentation and pixel-wise contrastive learning for medical image analysis. IEEE Trans. on Medical Imaging, 2024.
7. Y Zhang, C Peng, Q Wang, D Song, K Li, and S Kevin Zhou. Unified multi-modal image synthesis for missing MR sequence imputation. IEEE Trans. on Medical Imaging, 2024.
8. T Wu, C Huang, S Jia, W Li,R Chan,Tieyong Zeng, and SKevin Zhou. Medical imagere construction with multi-level deep learning denoiser and tight frame regularization. Applied Mathematics and Computation, 47(15), September 2024.
9. Q Quan, Q Yao, H Zhu, Q Wang, and S Kevin Zhou. Which images to label for few-shot medical image analysis? Medical Image Analysis, 2024.
10. Z Xu, J Li, Q Yao, H Li, M Zhao, and S Kevin Zhou. Addressing fairness issues in deep learning-based medical image analysis: A systematic review. npj Digital Medicine, 2024. (10.1038/s41746-024-01276-5)
11. Y Cao, Y Feng, H Wang, X Xie, and S Kevin Zhou. Learning to sketch: A neural approach to item frequency estimation in streaming data. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2024.
12. Z Huang, H Li, S Shao, H Zhu, H Hu, Z Cheng, J Wang, and S Kevin Zhou. PELE scores: Pelvic X-ray landmark detection with pelvis extraction and enhancement. International Journal of Computer Assisted Radiology and Surgery, 2024.
13. J Wang, S Song, X Wang, Y Wang, YMiao, J Su, and S Kevin Zhou. ProMISe: Promptable medical image segmentation using SAM. NeurIPS AIM-FM Workshop, 2024.
14. R Jin, Z Xu, Y Zhong, Q Yao, Q Dou, S Kevin Zhou, and X Li. FairMedFM: Fairness benchmarking for medical imaging foundation models. NeurIPS, 2024. (Datasets and Benchmarks Track)
15. X Liu, J Wang, S Kevin Zhou, C Engstrom, and S Chandra. Evidence-aware multi-modal data fusion and its application to total knee replacement prediction. International Conference on Digital Image Computing: Techniques and Applications (DICTA), Perth, Australia, 2024.
16. Y Huo, Y Shi, J Feng, Z Tao, Z Huang, L Yang, N Liu, L He, and S Kevin Zhou. CA-SAM: Enhancing the segment anything model in medical image segmentation with bi-group clicks guidance and lightweight adapter. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024.
17. Y Li, S Yang, X Wu, S He, and S Kevin Zhou. Taming stable diffusion for MRI cross-modality translation. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024.
18. Y Deng, C Wang, et al. and S Kevin Zhou. CTSpine1K: A large-scale dataset for spinal vertebrae seg mentation in computed tomography. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Open Data, Marrakesh, Morocco, 2024.
19. Z Zhao, F Feng, X Yang, Q Xu, C Guan, and S Kevin Zhou. See, predict, plan: Diffusion for procedure planning in robotic surgical videos. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Marrakesh, Morocco, 2024.
20. H Zhang, M Zhao, M Liu, J Luo, Y Guan, J Zhang, Y Xia, D Zhang, X Zhou, L Fan, S Liu, and S Kevin Zhou. Hierarchical multiple instance learning for COPD grading with relatively specific similarity. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Marrakesh, Morocco, 2024.
21. X Fu, YLi, F Tang, J Li, M Zhao, GTeng, and S Kevin Zhou. 3DGR-CAR:Coronary artery reconstruction from ultra-sparse 2D X-ray views with a 3D Gaussians representation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Marrakesh, Morocco, 2024.
22. X Wang, Z Xu, H Zhu, Q Yao, Y Sun, and S Kevin Zhou. SIX-Net: Spatial-context information mix-up for electrode landmark detection. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Marrakesh, Morocco, 2024. (early accepted)
23. F Tang, R Xu, Q Yao, X Fu, Q Quan, H Zhu, Z Liu, and S Kevin Zhou. HySparK: Hybrid sparse masking for large scale medical image pre-training. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Marrakesh, Morocco, 2024. (early accepted)
24. Y Rong, C Feng, X Xie, and S Kevin Zhou. Partial optimal transport based out-of-distribution detection for open-set semi-supervised learning. The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, 2024.
25. Q Li, X Xie, C Wang, and S Kevin Zhou. Prompt learning with extended Kalman filter for pre-trained language models. The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, 2024.
26. X Wang, Z Xu, Q Yao, Y Sun, and S Kevin Zhou. OFELIA: Optical flow-based electrode localization. Medical Imaging with Deep Learning (MIDL), Paris, France, 2024.
27. Q Quan, F Tang, Z Xu, H Zhu, and S Kevin Zhou. Slide-SAM: Medical SAM meets sliding window. Medical Imaging with Deep Learning (MIDL), Paris, France, 2024. (full score in the blind reviewing round)
28. H Lai, Q Yao, Z Jiang, R Wang, Z He, X Tao, and S Kevin Zhou. CARZero: Cross-attention alignment for radiology zero-shot classification. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, 2024.
29. Z Ding, Y Xiang, S Wang, X Xie, and S Kevin Zhou. Play like a vertex: A Stackelberg game approach for streaming graph partitioning. ACM SIGMOD Conference, Santiago, Chile, 2024.
30. W Chen, C Feng, A Ke, X Xie, and S Kevin Zhou. Out-of-distribution detection for learning-based chest X-ray diagnosis. International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, 2024.
31. D Sun, L Li, Z Zhang, H Qiu, S Zhao, and S Kevin Zhou. DNA-DIR: 2D-3D geometry embedding for intraoperative partial-to-full registration. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. (oral, 1/12 Finalists for Best Paper Award in Oral Presentations)
32. H Lai, Q Yao, Z He, X Tao, and S Kevin Zhou. Long-tailed multi-label classification with noisy label of thoracic diseases from chest X-ray. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. (oral)
33. F Tang, J Ding, Q Quan, L Wang, C Ning, and S Kevin Zhou. CMUNeXt: An efficient medical image seg mentation network based on large kernel and skip fusion. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. (oral)
34. ZGao and SKevin Zhou. Rethinking dual-domain undersampled MRI reconstruction: Domain-specific design from the perspective of the receptive field. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. (oral)
35. C Wang, Y Gu, P Liu, S Zhang, and S Kevin Zhou. E-DM: Evaluating diffusion model by conformal prediction. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024.
36. Q Yao, Z He, X Yu and S Kevin Zhou. Nowhere to hide: Toward robust reactive medical adversarial defense. International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024. (oral)
37. Y Feng, Y Cao, W Hairu, X Xie, and S Kevin Zhou. Mayfly: A neural data structure for graph stream summarization. The 12th International Conference on Learning Representations (ICLR), Vienna, Austria, 2024. (spotlight)
38. J Wei, S Kevin Zhou, S Cui and Z Li. WeakPCSOD: Overcoming the bias of box annotations for weakly supervised point cloud salient object detection. The 38th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
39. J Wang, S Song, J Su, and S Kevin Zhou. Distortion-disentangled contrastive learning. Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, 2024. (oral)
40. H Zhu, F Tang, Q Quan, K Chen, P Xiong, S Kevin Zhou, Deep generalizable prediction of RNA secondary structure via base pair motif energy, bioRxiv, 2024.10. 22.619430
41. G Funka-Lea, H Liao, S Kevin Zhou, Y Zheng, Y Tang, Three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, US Patent App. 18/477,593
2023:
1. S Kevin Zhou and Q Wang. Deep reinforcement learning in medical imaging. Deep Learning for Medical Image Analysis (Second Edition), S. Kevin Zhou, G. Hayit, and D. Shen (Eds.), Academic Press, 2023.
2. Q Yao, Z He, Y Li, Y Lin, K Ma, YZhengandSKevinZhou. Adversarial medical image with hierarchical feature hiding. IEEE Trans. on Medical Imaging, 2023.
3. H Yang, Q Wang, Y Zhang, Z An, L Chen, X Zhang, and S Kevin Zhou. Lung nodule segmentation and uncertain region prediction with an uncertainty-aware attention mechanism. IEEE Trans. on Medical Imaging, 2023.
4. B Zhou, H Xie, Q Liu, X Chen, X Guo, Z Feng, J Hou, S Kevin Zhou, B Li, A Rominger, K Shi, J Duncan, and C Liu. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical Image Analysis, 2023.
5. D Yang, Q Sun, C Wang, Y Wang, and S Kevin Zhou. TRCA-Net: Using TRCA filters to boost SSEVP classification with convolutional neural network. Journal of Neural Engineering, 2023.
6. C Peng, WA Lin, H Liao, R Chellappa, and S Kevin Zhou. Deep slice interpolation via marginal super resolution, fusion, and refinement. State of the Art in Neural Networks and Their Applications, AS El-Baz and JS Suri (Eds.), Academic Press, 2023.
7. Y Liu, S Zhao, et al. S Kevin Zhou, and R Liu. Multi-level effective surgical workflow recognition in robotic left lateral sectionectomy with deep learning: Experimental research. International Journal of Surgery, 2023. (PMID: 37318860)
8. G Zhang, C Bao, Y Liu, Z Wang, L Du, Y Zhang, F Wang, B Xu, S Kevin Zhou, and R Liu. 18F-FDG PET/CT-based deep learning model for fully automated prediction of pathological grading for pancreatic ductal adenocarcinoma before surgery. EJNMMI Research, 13(1):49, May 2023. (PMID: 37231321)
9. Y Zhang, C Peng, R Tong, L Lin, Y-W Chen, Q Chen, H Hu, and S Kevin Zhou. Multi-modal tumor seg mentation with deformable aggregation and uncertain region inpainting. IEEE Trans. on Medical Imaging, 42(10):3091-310, 2023.
10. R Yan, Y Shen, X Zhang, P Xu, J Wang, J Li, F Ren, D Ye, and S Kevin Zhou. Histopathological bladder cancer gene mutation prediction with hierarchical deep multiple-instance learning. Medical Image Analysis, 87:102824, July 2023.
11. W Ma, L Luo, K Liang, T Liu, J Su, Y Wang, J Li, S Kevin Zhou and N Shyh-Chang. XAI-enabled neural network analysis of metabolite spatial distributions. Analytical and Bioanalytical Chemistry, 415(14):2819 2830, June 2023.
12. P Qiao, H Li, G Song, H Han, Z Gao, Y Tian, Y Liang, X Li, S Kevin Zhou, and J Chen. Semi-supervised CTlesion segmentation using uncertainty-based data pairing and SwapMix. IEEE Trans. on Medical Imag ing, 42(5):1546- 1562, 2023.
13. S Yang, X Wu, S Ge, Z Zheng, S Kevin Zhou and L Xiao. Radiology report generation with a learned knowledge base and multi-modal alignment. Medical Image Analysis, 86:102798, May 2023.
14. J Li, J Chen, Y Tang, BLandman, andSKevinZhou. Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives. Medical Image Analysis, 85:102762, April 2023. (414 references)
15. C You, W Dai,Y Min, F Liu, X Zhang, DA Clifton, S Kevin Zhou, L Staib,and J Duncan. Rethinking semi supervised medical image segmentation: A variance-reduction perspective. Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023.
16. Q Wu, L Cheng, C Wang, H Wei, S Kevin Zhou, J Yu, and Y Zhang. Unsupervised polychromatic neural representation for CT metal artifact reduction. Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2023.
17. C Wang, K Shang, H Zhang, S Zhao, D Liang, and S Kevin Zhou. Active CT reconstruction with a learned sampling policy. ACM Multimedia, Ottawa, Canada, 2023.
18. Y Li and S Kevin Zhou. Retrieve2Segment: Patch retrieval for performant zero-shot cross-modality seg mentation. Big Task Small Data, 1001-AI Workshop, Vancouver, Canada, 2023.
19. J Li, K Li, Y Zhou and S Kevin Zhou. O2CTA: Introducing annotations from OCT to CCTA in coronary plaque analysis. Big Task Small Data, 1001-AI Workshop, Vancouver, Canada, 2023.
20. L Chen, H Li, and S Kevin Zhou. Label-free nuclei segmentation using intra-image self similarity. Interna tional Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, 2023.
21. Z Xu, S Zhao, Q Quan, Q Yao, and S Kevin Zhou. FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, 2023.
22. P Zhao, H Li, R Jin, and S Kevin Zhou. DiffULD: Diffusive universal lesion detection. International Con ference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, 2023.
23. H Zhu, Q Quan, Q Yao, Z Liu, and S Kevin Zhou. UOD: Universal one-shot detection of anatomical landmarks. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, 2023.
24. J Wei, Y Hu, S Cui, S Kevin Zhou, and Z Li. WeakPolyp: You only look bounding box for polyp seg mentation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver, Canada, 2023.
25. S Shao, X Yuan, Z Huang, Z Qiu, S Wang, and S Kevin Zhou. DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models. The 1st International Workshop on Generalizing from Limited Resources in the Open World, Macao, China, 2023.
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]
