Personal Information

ZHUANG, Xiahai (PhD)

Assistant Dean
School of Data Science
Fudan University


I obtained my PhD (thesis) from the Centre for Medical Image Computing, University College London, with Prof. S Ourselin and Prof. D J Hawkes. My master (SJTU) and bachelor (TJU) degrees were both from computer science.


Visit our ZMIC Lab → s/w, code/data → LAScarQS todo
MyoPS 2020 NEW!!! → MS-CMRSeg 2019 → MM-WHS 2017→

Research interests

★ Medical image analysis (AI-assisted diagnosis & therapy)
★ Computer vision, image processing and visualization
☆ Image registration, segmentation and modeling
☆ Image super resolution, restoration and reconstruction


☆ DATA630015 Medical Image Analysis & Application (postgrad)
☆ DATA620018 Data Visualization: App. & Implement. (postgrad)
☆ DATA130049 Image Processing & Visualization (undergrad)
☆ DATA130012 Image Processing & Data Visualization (undergrad)

Academic Service

★ Associate Editor or Medical Image Analysis, Impact Factor: 11.148
    Editorial Board Member Computers in Biology and Medicine
★ PC/AC/SC for conferences MICCAI, ISBI, FIMH, MIDL etc.

Selected projects (grants)

  • Methodologies and applications of combined segmentation of multimodality cardiac images based on multivariate mixture model; National Natural Science Foundation of China; 2020-2023; PI
  • The projects sponsored by the development fund for Shanghai talents (2020015); 2020-2023; PI
  • Cardiac Image Segmentation via Deep Learning with Regularization using Prior Sub-Networks; NSFC-NRF: 2020-2022; PI
  • Early diagnosis of AD using big neuroimaging data and deep network; Science and Technology Commission of Shanghai Municipality; 2017-2019; PI
  • High-Performance Image Registration Algorithms for Prostate Cancer Intervention, National Natural Science Foundation of China and Royal Society U.K., 2015/04-2017/03, PI
  • Evaluation of micro vessel prostate cancer with T1-DCE and T2*-DSC, Medicine-Engineering/ Science Interdisciplinary research grant, 2015/01-2017/12, Co-PI
  • Extracting clinically useful information from cardiac MR images using large-scale machine learning, Newton Research Collaboration Programme 2015, Co-PI
  • Fast nonrigid registration based on spatial information encoded mutual information and the clinical applications; National Natural Science Foundation of China; 2014/01-2016/12, PI
  • Using medical images for assisting cardiac functional analysis and early diagnosis of heart diseases; RF ROCS, State Education Ministry of China; 2014/01-2016/12, PI

Selected Publications

  • for complete publication list pls refer to gscholar, for code/data pls refer to zmic proj
  • S Gao & X Zhuang*: Rank-One Network: An Effective Framework for Image Restoration. IEEE Transactions on Pattern Analysis and Machine Intelligence (T PAMI) (Impact Factor: 17.86) 2020-12 link NEW!!!
  • X Zhuang: Multivariate mixture model for myocardial segmentation combining multi-source images. IEEE Transactions on Pattern Analysis and Machine Intelligence (IF: 17.86) 41(12), 2933-2946, 2019. link
    code note&demo
  • C Pei, F Wu, L Huang, X Zhuang. Disentangle domain features for cross-modality cardiac image segmentation. Medical Image Analysis 2021 link NEW!!!
  • F Wu & X Zhuang*: CF Distance: A new domain discrepancy metric and application to explicit domain adaptation for cross-modality cardiac image segmentation. IEEE Transactions on Medical Imaging 39 (12), 4274 - 4285, 2020 link
    code data
  • L Li et al. & X Zhuang*: Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts Framework. Medical Image Analysis (IF: 11.148) 60, 2020 link
  • X Zhuang et al.: Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge. Medical Image Analysis (IF: 11.148) 58, 2019 (most downloaded Medical Image Analysis articles) link
  • X Zhuang & J Shen: Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI. Medical Image Analysis (IF: 11.148) 31, 77–87, 2016 (most cited Medical Image Analysis articles) link
  • D Jia & X Zhuang*: Learning-Based Algorithms for Vessel Tracking: A Review. Computerized Medical Imaging and Graphics 2021 link
  • X Zhuang: Challenges and Methodologies of Fully Automatic Whole Heart Segmentation: A Review. Journal of Healthcare Engineering 4 (3): 371–407, 2013 pdf
  • X Zhuang et al.: A Nonrigid Registration Framework Using Spatially Encoded Mutual Information and Free-Form Deformations. IEEE Transactions on Medical Imaging, 30(10), 1819-1828, 2011.   link pdf
  • X Zhuang et al.: A Registration-Based Propagation Framework for Automatic Whole Heart Segmentation of Cardiac MRI. IEEE Transactions on Medical Imaging, 29 (9), 1612-1625, 2010.   link pdf
  • X Zhuang et al.: An atlas-based segmentation propagation framework using locally affine registration – Application to automatic whole heart segmentation. MICCAI2008, 425-433.   link (runner-up for MICCAI Young Scientist Award)