Minghui Zhang 张明辉

PhD student @ IMR, SJTU
minghuizhang [at] sjtu [dot] edu [dot] cn
I am a Ph.D. candidate at the Institute of Medical Robotics, Shanghai Jiao Tong University, supervised by Prof. Yun Gu and Prof. Guang-Zhong Yang.
Before coming to SJTU, I earned a bachelor’s degree in Automation from Southeast University, graduating as an outstanding graduate, under the supervision of Prof. Hong Pan. I also interned at the Hospital for Skin Diseases, Chinese Academy of Medical Sciences, supervised by Prof. Siyu Xia. We built a large pixel-annotated vitiligo dataset collected by wood lamp and developed the quantification pipeline for supporting diagnosis and follow-up research.
I previously collaborated with
Dr. Puyang Wang, Dr. Dakai Jin, and Prof. Le Lu of the DAMO Academy on topology-guided pulmonary airway modeling. Meanwhile, I have also had the opportunity to collaborate with Dr.Kaiyuan Yang from the Department of Quantitative Biomedicine at the University of Zurich, led by Prof. Bjoern Menze , on exploring the Circle of Willis in the brain.
My research focuses on AI for Medical Imaging
and AI for Healthcare
, with a particular emphasis on advancing medical robotics for preoperative planning, intraoperative navigation, and intelligent surgical decision support. Our goal is to develop intelligent systems that enhance surgical precision, reduce procedure times, and improve patient safety.
news
Jul 2025 | Benchmarking the CoW with the TopCoW Challenge has been updated, welcome to follow! |
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Jun 2025 | Start the internship in Shanghai Artificial Intelligence Laboratory, supervised by Prof. Yihao Liu. |
Jun 2025 | Awarded the Grand Prize in the algorithm challenge organized by ZTE Corporation (rank 1/20,000+, 250,000 RMB). |
May 2025 | Our co-organized MICCAI 2025 TopBrain Challenge is now open for registration. We warmly welcome you to join and participate! |
May 2025 | One co-author paper is accepted by MICCAI 2025! |
selected publications
- MICCAI WorkshopFda: Feature decomposition and aggregation for robust airway segmentationIn Domain Adaptation and Representation Transfer @ MICCAI, MICCAI Workshop, 2021
- MedIATrustworthy learning with (un) sure annotation for lung nodule diagnosis with CTMedical Image Analysis, 2023
- IEEE TMIAccurate airway tree segmentation in ct scans via anatomy-aware multi-class segmentation and topology-guided iterative learningIEEE transactions on medical imaging, 2024
- IEEE JBHISLoRD: Structural Low-Rank Descriptors for Shape Consistency in Vertebrae SegmentationIEEE Journal of Biomedical and Health Informatics, 2025
- MICCAISemantic difference guidance for the uncertain boundary segmentation of CT left atrial appendageIn International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023
- MICCAI
- IJCARSReflecting topology consistency and abnormality via learnable attentions for airway labelingInternational Journal of Computer Assisted Radiology and Surgery, 2025