MSDF-Net: Multi-Scale Deep Fusion Network for Stroke Lesion Segmentation. - Xinfeng Liu; Hao Yang 026; Kehan Qi; Pei Dong; Qiegen Liu; Xin Liu 053; Rongpin Wang; Shanshan Wang 002 (IEEE Access, 2019)

A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint. - Weijian Huang; Hao Yang 026; Xinfeng Liu; Cheng Li 008; Ian Zhang 002; Rongpin Wang; Hairong Zheng; Shanshan Wang 002 (CoRR, 2020)

AIDE: Annotation-efficient deep learning for automatic medical image segmentation. - Cheng Li 008; Rongpin Wang; Zaiyi Liu; Meiyun Wang; Hongna Tan; Yaping Wu; Xinfeng Liu; Hui Sun; Rui Yang; Xin Liu 053; Ismail Ben Ayed; Hairong Zheng; et al. (CoRR, 2020)

A Learning-Based Model to Evaluate Hospitalization Priority in COVID-19 Pandemics. - Yichao Zheng; Yinheng Zhu; Mengqi Ji; Rongpin Wang; Xinfeng Liu; Mudan Zhang; Jun Liu; Xiaochun Zhang; Choo Hui Qin; Lu Fang 001; Shaohua Ma (Patterns, 2020)

FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms. - Zhenxing Huang; Xinfeng Liu; Rongpin Wang; Mudan Zhang; Xianchun Zeng; Jun Liu 080; Yongfeng Yang; Xin Liu 053; Hairong Zheng; Dong Liang 001; Zhanli Hu (Appl. Intell., 2021)

An AI-based radiomics nomogram for disease prognosis in patients with COVID-19 pneumonia using initial CT images and clinical indicators. - Mudan Zhang; Xianchun Zeng; Chencui Huang; Jun Liu; Xinfeng Liu; Xingzhi Xie; Rongpin Wang (Int. J. Medical Informatics, 2021)

Considering anatomical prior information for low-dose CT image enhancement using attribute-augmented Wasserstein generative adversarial networks. - Zhenxing Huang; Xinfeng Liu; Rongpin Wang; Jincai Chen; Ping Lu 006; Qiyang Zhang; Changhui Jiang; Yongfeng Yang; Xin Liu 053; Hairong Zheng; Dong Liang 001; Zhanli Hu (Neurocomputing, 2021)

Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network. - Zihao Bo; Hui Qiao; Chong Tian; Yuchen Guo; Wuchao Li; Tiantian Liang; Dongxue Li; Dan Liao; Xianchun Zeng; Leilei Mei; Tianliang Shi; Bo Wu; et al. (Patterns, 2021)

Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites. - Zhenxing Huang; Xinfeng Liu; Rongpin Wang; Zixiang Chen; Yongfeng Yang; Xin Liu 053; Hairong Zheng; Dong Liang 001; Zhanli Hu (IEEE J. Biomed. Health Informatics, 2021)

2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-Center Study. - Lingwei Meng; Di Dong; Xin Chen 058; Mengjie Fang; Rongpin Wang; Jing Li; Zaiyi Liu; Jie Tian 001 (IEEE J. Biomed. Health Informatics, 2021)

Multi-Focus Network to Decode Imaging Phenotype for Overall Survival Prediction of Gastric Cancer Patients. - Liwen Zhang; Di Dong; Lianzhen Zhong; Cong Li; Chaoen Hu; Xin Yang 001; Zaiyi Liu; Rongpin Wang; Junlin Zhou; Jie Tian 001 (IEEE J. Biomed. Health Informatics, 2021)

A Coarse-to-Fine Deformable Transformation Framework for Unsupervised Multi-Contrast MR Image Registration with Dual Consistency Constraint. - Weijian Huang; Hao Yang 026; Xinfeng Liu; Cheng Li 008; Ian Zhang 002; Rongpin Wang; Hairong Zheng; Shanshan Wang 002 (IEEE Trans. Medical Imaging, 2021)

StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images. - Bangkang Fu; Mudan Zhang; Junjie He; Ying Cao; Yuchen Guo; Rongpin Wang (Comput. Methods Programs Biomed., 2022)

ASSURED: A Self-Supervised Deep Decoder Network for Fetus Brain MRI Reconstruction. - Jiangjie Wu; Lixuan Chen; Zhenghao Li; Lihui Wang; Rongpin Wang; Hongjiang Wei; Yuyao Zhang (ISBI, 2023)

msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping. - Junjie He; Yunsong Peng; Bangkang Fu; Yuemin Zhu; Lihui Wang 002; Rongpin Wang (NeuroImage, 2023)

A robust and efficient AI assistant for breast tumor segmentation from DCE-MRI via a spatial-temporal framework. - Jiadong Zhang; Zhiming Cui; Zhenwei Shi; Yingjia Jiang; Zhiliang Zhang; Xiaoting Dai; Zhenlu Yang; Yuning Gu; Lei Zhou 003; Chu Han; Xiaomei Huang; Chenglu Ke; et al. (Patterns, 2023)

Deep wavelet scattering orthogonal fusion network for glioma IDH mutation status prediction. - Qijian Chen; Lihui Wang 002; Zhiyang Xing; Li Wang 169; Xubin Hu; Rongpin Wang; Yue-Min Zhu (Comput. Biol. Medicine, 2023)

A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly. - Mudan Zhang; Xuntao Yin; Wuchao Li; Yan Zha; Xianchun Zeng; Xiaoyong Zhang; Jingjing Cui; Zhong Xue; Rongpin Wang; Chen Liu (BMC Medical Imaging, 2023)

TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma. - Xinhuan Sun; Wuchao Li; Bangkang Fu; Yunsong Peng; Junjie He; Lihui Wang; Tongyin Yang; Xue Meng; Jin Li; Jinjing Wang; Ping Huang; Rongpin Wang (Comput. Methods Programs Biomed., 2023)

mQSM: Multitask Learning-Based Quantitative Susceptibility Mapping for Iron Analysis in Brain. - Junjie He; Bangkang Fu; Zhenliang Xiong; Yunsong Peng; Rongpin Wang (MICCAI (2), 2024)

3D convolutional network with edge detection for prostate gland and tumor segmentation on T2WI and ADC. - Chongzhe Yan; Feng Liu; Yunsong Peng; Yuanshen Zhao; Junjie He; Rongpin Wang (Biomed. Signal Process. Control., 2024)

Multicenter evaluation of CT deep radiomics model in predicting Leibovich score risk groups for non-metastatic clear cell renal cell carcinoma. - Wuchao Li; Tongyin Yang; Pinhao Li; Xinfeng Liu; Shasha Zhang; Jianguo Zhu 003; Yuanyuan Pei; Yan Zhang 109; Tijiang Zhang; Rongpin Wang (Displays, 2024)

A hybrid classification model with radiomics and CNN for high and low grading of prostate cancer Gleason score on mp-MRI. - Feng Liu; Yuanshen Zhao; Jukun Song; Guilan Tu; Yadong Liu; Yunsong Peng; Jiahui Mao; Chongzhe Yan; Rongpin Wang (Displays, 2024)

Identifying pathological groups from MRI in prostate cancer using graph representation learning. - Feng Liu; Yuanshen Zhao; Chongzhe Yan; Jingxian Duan; Lei Tang; Bo Gao; Rongpin Wang (Displays, 2024)

A nutrition-based radiomics-clinical model to predict the prognosis of patients with acute-on-chronic liver failure. - Qian Zhang; Yunsong Peng; Siyi Lei; Tingting Xiong; Liulu Zhang; Hong Peng; Xinhua Luo; Rongpin Wang (Displays, 2024)

SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images. - Junjie He; Mudan Zhang; Wuchao Li; Yunsong Peng; Bangkang Fu; Chen Liu 026; Jian Wang 135; Rongpin Wang (Comput. Biol. Medicine, 2024)

HmsU-Net: A hybrid multi-scale U-net based on a CNN and transformer for medical image segmentation. - Bangkang Fu; Yunsong Peng; Junjie He; Chong Tian; Xinhuan Sun; Rongpin Wang (Comput. Biol. Medicine, 2024)

ACE-QSM: Accelerating quantitative susceptibility mapping acquisition using diffusion models by reducing repetition time. - Junjie He; Bangkang Fu; Bo Wang; Yunsong Peng; Lisha Nie; Man Tang; Rui Xu; Rongpin Wang (Biomed. Signal Process. Control., 2025)

Segmentation outperforms registration in quantitative analysis of brain iron. - Junjie He; Bangkang Fu; Bo Wang; Zhenliang Xiong; Yunsong Peng; Rongpin Wang (Biomed. Signal Process. Control., 2025)

GAMMIL: A graph attention-guided multi-scale fusion multiple instance learning model for the WHO grading of meningioma in whole slide images. - Guilan Tu; Wuchao Li; Yongshun Lin; Zi Xu; Junjie He; Bangkang Fu; Ping Huang; Rongpin Wang; Yunsong Peng (Biomed. Signal Process. Control., 2025)

Convolutional state space model with multi-window cross-scan to advance the automated diagnosis of skeletal fluorosis. - Hao Xu 041; Yun Wu; Rui Xie; Jun Xu; Junpeng Wu; Rongpin Wang; Youliang Tian (Biomed. Signal Process. Control., 2025)

BMA-Net: A 3D bidirectional multi-scale feature aggregation network for prostate region segmentation. - Bangkang Fu; Feng Liu; Junjie He; Zi Xu; Yunsong Peng; Xiaoli Zhang; Rongpin Wang (Comput. Methods Programs Biomed., 2025)

RPF-Net: A multimodal model for the postoperative UISS risk stratification of non-metastatic ccRCC based on CT and whole-slide images. - Jiahui Mao; Wuchao Li; Xinhuan Sun; Bangkang Fu; Junjie He; Chongzhe Yan; Jianguo Zhu 003; Zhuxue Zhang; Jiahui Mao; Zhangxin Hong; Qi Tang; Zhen Liu; et al. (Comput. Methods Programs Biomed., 2025)

PcPreT-Net: Predicting classification of decline rate in prostate-specific antigen using graph neural network. - Chongzhe Yan; Feng Liu; Ying Cao; Huijuan Tu; Zi Xu; Wuchao Li; Pinhao Li; Zhiyang Xing; Yi Chen; Zhi-Cheng Li; Yuanshen Zhao; Bo Gao; et al. (Displays, 2025)

Masked latent transformer with random masking ratio to advance the diagnosis of dental fluorosis. - Hao Xu 041; Yun Wu; Junpeng Wu; Rui Xie; Maohua Gu; Rongpin Wang (J. Vis. Commun. Image Represent., 2025)

Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping. - Qijian Chen; Lihui Wang 002; Zeyu Deng; Rongpin Wang; Li Wang 169; Caiqing Jian; Yue-Min Zhu (Medical Image Anal., 2025)

HGTL: A hypergraph transfer learning framework for survival prediction of ccRCC. - Xiangmin Han; Wuchao Li; Yan Zhang 109; Pinhao Li; Jianguo Zhu 003; Tijiang Zhang; Rongpin Wang; Yue Gao 002 (Medical Image Anal., 2025)

SUFFICIENT: A scan-specific unsupervised deep learning framework for high-resolution 3D isotropic fetal brain MRI reconstruction. - Jiangjie Wu; Lixuan Chen; Zhenghao Li; Xin Li; Saban Öztürk; Lihui Wang; Rongpin Wang; Hongjiang Wei; Yuyao Zhang (CoRR, 2025)

Magnetic resonance imaging for noninvasive assessment of renal fat deposition and hypoxia in diabetic kidney disease. - Jian Liu; Daoyu Yang; Chong Tian; Rui Lv; Rongpin Wang; Xianchun Zeng (BMC Medical Imaging, 2025)