Dr. Xuming Zhang | Biomedical Engineering | Best Researcher Award

Dr at Huazhong University of Science and Technology, China.

Xuming Zhang is an Associate Professor in the Department of Biomedical Engineering at Huazhong University of Science and Technology. Born on November 21, 1976, he specializes in medical image processing, AI for medical diagnosis, surgical guidance, and surgical robots. He earned his Ph.D. in Biomedical Engineering from Shanghai Jiaotong University and completed postdoctoral research at UC Davis and Huazhong University. Dr. Zhang has led significant research projects, including early prostate cancer diagnosis and real-time 3D ultrasound-MR image registration. His work has earned him multiple awards, including the Hubei Science and Technology Progress Award.

 

Profile

 

Scopus

 

🎓 Education 

Ph.D. in Biomedical Engineering, Shanghai Jiaotong University (2001.3-2005.11) Tutor: Academician Binshi Xu. Master’s in Biomedical Engineering, Wuhan University of Technology (1998.9-2001.2). Bachelor’s in Biomedical Engineering, Wuhan University of Technology (1994.9-1998.6)

🧑‍🏫 Professional Experience

2008.1-2009.1: Post-doctoral Fellow, Department of Mechanical and Aeronautical Engineering, University of California at Davis. 2006.1-2008.1: Post-doctoral Fellow, State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology
Tutor: Academician Youlun Xiong

📊 Research Projects 📊

Research on Early Prostate Cancer Diagnosis Technology National Key Research and Development Program, 2020.10-2023.09, ¥8.82 million. Real-time Accurate Registration of 3D Ultrasound and MR Images for Prostate Targeted Biopsy Based on Deep Learning Sponsored by National Natural Science Foundation of China, 2019.01-2022.12, ¥0.57 million. Research and Development of Surgery Planning and Navigation System Based on CT-3D Ultrasound Fusion National Key Research and Development Program, 2017.12-2020.11, ¥1.53 million. Nondestructive Testing of Quality Status of Retired Products Based on the Combination of Electromagnetic Ultrasound and Eddy Current 863 Project, 2013.01-2015.12, ¥0.4 million. Research on Non-local Elastic Registration of Prostate Ultrasound and PET Images for Prostate Biopsy Wuhan Science and Technology Bureau Project, 2015.03-2016.12, ¥0.15 million. Multi-DOF Prostate Biopsy Robot Enterprise Project, 2016.03-2019.03, ¥1.5 million. Research and Development of High-Frequency Composite Ultrasonic Scanning Probe Microscopy National Major Instrument Project, 2013.10-2017.09, ¥4.4949 million. Research and Development of 3D Ultrasonic System for the Diagnosis and Treatment of Urinary Diseases National Science and Technology Support Program, 2012.01-2014.12, ¥5.506 million Key Technologies of Real-Time Three-Dimensional Ultrasound Imaging International Science and Technology Cooperation Project, 2013.04-2016.03, ¥4.75 million

🏆 Awards 

Innovation and Application of Key Technologies in Diagnosis and Treatment of Renal Cancer First Prize, Hubei Science and Technology Progress Award (Rank: 4th). Innovation and Application of Key Technologies in Diagnosis and Treatment of Renal Cancer Third Prize, Chinese Medical Science and Technology Award (Rank: 4th)

Publication:📝

1. A temporal enhanced semi-supervised training framework for needle segmentation in 3D ultrasound images

• Authors: Wen, M.; Shcherbakov, P.; Xu, Y.; Yuan, L.; Zhang, X.
• Journal: Physics in Medicine and Biology
• Volume: 69
• Issue: 11
• Article: 115023
• Access: Open Access
• Citations: 0

 

 

2. CIRF: Coupled Image Reconstruction and Fusion Strategy for Deep Learning Based Multi-Modal Image Fusion

• Authors: Zheng, J.; Xiao, J.; Wang, Y.; Zhang, X.
• Journal: Sensors
• Volume: 24
• Issue: 11
• Article: 3545
• Access: Open Access
• Citations: 0

 

 

3. Robust Semi-Supervised 3D Medical Image Segmentation With Diverse Joint-Task Learning and Decoupled Inter-Student Learning

• Authors: Zhou, Q.; Yu, B.; Xiao, F.; Wang, Z.; Zhang, X.
• Journal: IEEE Transactions on Medical Imaging
• Volume: 43
• Issue: 6
• Pages: 2317-2331
• Citations: 0

 

4. TransVFS: A spatio-temporal local–global transformer for vision-based force sensing during ultrasound-guided prostate biopsy

• Authors: Wang, Y.; Ye, Z.; Wen, M.; Liang, H.; Zhang, X.
• Journal: Medical Image Analysis
• Volume: 94
• Article: 103130
• Citations: 1

 

5. SPCTNet: A Series-Parallel CNN and Transformer Network for 3D Medical Image Segmentation

• Authors: Yu, B.; Zhou, Q.; Zhang, X.
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Volume: 14473
• Pages: 376-387
• Citations: 0

 

6. Short-term and long-term memory self-attention network for segmentation of tumours in 3D medical images

• Authors: Wen, M.; Zhou, Q.; Tao, B.; Xu, Y.; Zhang, X.
• Journal: CAAI Transactions on Intelligence Technology
• Volume: 8
• Issue: 4
• Pages: 1524-1537
• Access: Open Access
• Citations: 7

 

7. Free form deformation and symmetry constraint-based multi-modal brain image registration using generative adversarial nets

• Authors: Zhu, X.; Ding, M.; Zhang, X.
• Journal: CAAI Transactions on Intelligence Technology
• Volume: 8
• Issue: 4
• Pages: 1492-1506
• Access: Open Access
• Citations: 2

 

8. F-DARTS: Foveated Differentiable Architecture Search Based Multimodal Medical Image Fusion

• Authors: Ye, S.; Wang, T.; Ding, M.; Zhang, X.
• Journal: IEEE Transactions on Medical Imaging
• Volume: 42
• Issue: 11
• Pages: 3348-3361
• Citations: 3

 

 

9. Medical Image Classification Using Light-Weight CNN With Spiking Cortical Model Based Attention Module

• Authors: Zhou, Q.; Huang, Z.; Ding, M.; Zhang, X.
• Journal: IEEE Journal of Biomedical and Health Informatics
• Volume: 27
• Issue: 4
• Pages: 1991-2002
• Citations: 13

 

 

10. Self-supervised transformer based non-local means despeckling of optical coherence tomography images

• Authors: Zhou, Q.; Wen, M.; Yu, B.; Ding, M.; Zhang, X.
• Journal: Biomedical Signal Processing and Control
• Volume: 80
• Article: 104348
• Access: Open Access
• Citations: 8