Prof. Yanjie Zhu | Algorithm Development | Best Researcher Award
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China
👨🎓Professional Profiles
🔬 Summary
Prof. Yanjie Zhu is a renowned expert in fast magnetic resonance imaging (MRI) and its applications in medical diagnostics. He specializes in developing innovative imaging techniques through machine learning, deep learning, and model-driven methods. As a Professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, he leads cutting-edge research projects focused on cardiovascular imaging, brain health, and intelligent diagnostic tools.
🎓 Education
Prof. Zhu earned his Ph.D. in Circuits and Systems from the Shanghai Institute of Technical Physics, Chinese Academy of Sciences, China (2006-2011). He also holds a B.S. in Electronic Engineering and Information Science from the University of Science and Technology of China, Hefei (2002-2006).
🏫 Professional Experience
Prof. Zhu has a distinguished academic career at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, where he progressed from Assistant Professor (2011-2015) to Associate Professor (2015-2020), and is currently a Professor (2020-present). Additionally, he served as a Visiting Scholar (2017-2018) at Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, under the guidance of Reza Nezafat.
📚 Academic Contributions
Prof. Zhu has published several impactful papers in the field of MRI and medical imaging. Notable works include:
- “Online reconstruction of fast dynamic MR imaging using deep low-rank plus sparse network,” IEEE CBMS, 2022.
- “k-space based reconstruction method for wave encoded bSSFP sequence,” CECIT, 2021.
- “Quantification of pectinate muscles inside left atrial appendage from CT images using fractal analysis,” ICMIPE, 2021.
- Myocardial Edema Imaging – A Comparison of Three Techniques, ISMRM 2018 (Power Pitch, Magna Cum Laude Merit Award).
🔍 Research Interests
Prof. Zhu’s research interests revolve around model-driven fast MRI techniques, generative model-based adaptive MRI methods, and diffusion tensor and edema imaging for myocardial and brain tissue. He is also focused on intelligent diagnosis for the early detection of stroke-related plaques and other cardiovascular conditions.
💻 Technical Skills
Prof. Zhu is highly skilled in MRI imaging techniques, including fast MRI, cardiac MRI, and brain MRI. He also excels in deep learning and AI-based image reconstruction methods, along with proficiency in medical imaging software and model-driven approaches. His expertise in data analysis and computational methods has contributed to advancing medical applications.
👨🏫 Teaching Experience
Throughout his career, Prof. Zhu has mentored and taught graduate students and professionals in the fields of MRI technology, medical imaging, and computational healthcare methods. His research-driven approach has helped develop comprehensive educational materials that support the training of professionals in advanced imaging systems.
📖Top Noted Publications
RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping
Authors: Chiyi Huang, Longwei Sun, Dong Liang, Haifeng Liang, Hongwu Zeng, Yanjie Zhu
Journal: Computers in Biology and Medicine
Year: 2024
High-Frequency Space Diffusion Model for Accelerated MRI
Authors: Chentao Cao, Zhuo-Xu Cui, Yue Wang, Shaonan Liu, Taijin Chen, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024
SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI
Authors: Zhuo-Xu Cui, Chentao Cao, Yue Wang, Sen Jia, Jing Cheng, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024
A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection
Authors: Wenxin Wang, Zhuo-Xu Cui, Guanxun Cheng, Chentao Cao, Xi Xu, Ziwei Liu, Haifeng Wang, Yulong Qi, Dong Liang, Yanjie Zhu
Journal: IEEE Journal of Biomedical and Health Informatics
Year: 2024
High efficiency free-breathing 3D thoracic aorta vessel wall imaging using self-gating image reconstruction
Authors: Caiyun Shi, Congcong Liu, Shi Su, Haifeng Wang, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: Magnetic Resonance Imaging
Year: 2024
Physics-Driven Deep Learning Methods for Fast Quantitative Magnetic Resonance Imaging
Authors: Yanjie Zhu, Jing Cheng, Zhuo-Xu Cui, et.al.
Journal: IEEE Signal Processing Magazine
Year: 2023