AHCNet: An Application of Attention Mechanism and Hybrid Connection for Liver Tumor Segmentation in CT Volumes. - Huiyan Jiang; Tianyu Shi 002; Zhiqi Bai; Liangliang Huang (IEEE Access, 2019)

A Stacked Generalization U-shape network based on zoom strategy and its application in biomedical image segmentation. - Tianyu Shi 002; Huiyan Jiang; Bin Zheng 001 (Comput. Methods Programs Biomed., 2020)

Improving the fidelity of CT image colorization based on pseudo-intensity model and tumor metabolism enhancement. - Zexu Zhang; Huiyan Jiang; Jiaji Liu; Tianyu Shi 002 (Comput. Biol. Medicine, 2021)

Multi-stage puncture path planning algorithm of ablation needles for percutaneous radiofrequency ablation of liver tumors. - Min Luo; Huiyan Jiang; Tianyu Shi 002 (Comput. Biol. Medicine, 2022)

PSR-Nets: Deep neural networks with prior shift regularization for PET/CT based automatic, accurate, and calibrated whole-body lymphoma segmentation. - Meng Wang 029; Huiyan Jiang; Tianyu Shi 002; Zhiguo Wang 001; Jia Guo; Guoxiu Lu; Youchao Wang; Yu-Dong Yao (Comput. Biol. Medicine, 2022)

A unified uncertainty network for tumor segmentation using uncertainty cross entropy loss and prototype similarity. - Zhaoshuo Diao; Huiyan Jiang; Tianyu Shi 002 (Knowl. Based Syst., 2022)

C2MA-Net: Cross-Modal Cross-Attention Network for Acute Ischemic Stroke Lesion Segmentation Based on CT Perfusion Scans. - Tianyu Shi 002; Huiyan Jiang; Bin Zheng 001 (IEEE Trans. Biomed. Eng., 2022)

HD-RDS-UNet: Leveraging Spatial-Temporal Correlation Between the Decoder Feature Maps for Lymphoma Segmentation. - Meng Wang 029; Huiyan Jiang; Tianyu Shi 002; Yu-Dong Yao (IEEE J. Biomed. Health Informatics, 2022)

ASE-Net: A tumor segmentation method based on image pseudo enhancement and adaptive-scale attention supervision module. - Junzhi Zhang; Huiyan Jiang; Tianyu Shi 002 (Comput. Biol. Medicine, 2023)

SCL-Net: Structured Collaborative Learning for PET/CT Based Tumor Segmentation. - Meng Wang 029; Huiyan Jiang; Tianyu Shi 002; Yu-Dong Yao (IEEE J. Biomed. Health Informatics, 2023)

A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation. - Huiyan Jiang; Zhaoshuo Diao; Tianyu Shi 002; Yang Zhou; Feiyu Wang; Wenrui Hu; Xiaolin Zhu; Shijie Luo; Guoyu Tong; Yu-Dong Yao (Comput. Biol. Medicine, 2023)

A spatial squeeze and multimodal feature fusion attention network for multiple tumor segmentation from PET-CT Volumes. - Zhaoshuo Diao; Huiyan Jiang; Tianyu Shi 002 (Eng. Appl. Artif. Intell., 2023)

Metabolic Anomaly Appearance Aware U-Net for Automatic Lymphoma Segmentation in Whole-Body PET/CT Scans. - Tianyu Shi 002; Huiyan Jiang; Meng Wang 029; Zhaoshuo Diao; Guoxu Zhang; Yu-Dong Yao (IEEE J. Biomed. Health Informatics, 2023)

MSU-Net: Multi-scale Sensitive U-Net based on pixel-edge-region level collaborative loss for nasopharyngeal MRI segmentation. - Yuanquan Hao; Huiyan Jiang; Zhaoshuo Diao; Tianyu Shi 002; Lizhi Liu; Haojiang Li; Weijing Zhang (Comput. Biol. Medicine, 2023)

Siamese semi-disentanglement network for robust PET-CT segmentation. - Zhaoshuo Diao; Huiyan Jiang; Tianyu Shi 002; Yu-Dong Yao (Expert Syst. Appl., 2023)

A Lightweight Network for Contextual and Morphological Awareness for Hepatic Vein Segmentation. - Guoyu Tong; Huiyan Jiang; Tianyu Shi 002; Xian-Hua Han; Yu-Dong Yao (IEEE J. Biomed. Health Informatics, 2023)

CAD-Net: a cross-phase attention-driven dual-task network for automated rectal cancer segmentation and lymph node metastasis diagnosis in dual-phase CT imaging. - Tianyu Shi 002; Xiaoyang Gu; Shuting Tai; Meng Wang 029; Yan Zhang; Chao Lv (Biomed. Signal Process. Control., 2026)

Dual GANs with contextual-dropout and pairwise-terms constraints for dual-phase CT scan synthesis in rectal cancer. - Tianyu Shi 002; Xiaoyang Gu; Shuting Tai; Yan Zhang (Biomed. Signal Process. Control., 2026)

Triplet-branch diffusion model with conditional guidance and boundary enhancement for cervical nucleus segmentation. - Tianyu Shi 002; Jia Tang; Yantao Sun; Zhimin Liu (Biomed. Signal Process. Control., 2026)