Medical image analysis, Computer-aided diagnosis, Machine learning

Xiangyuan, Lecturer, obtained bachelor's and doctoral degrees from Sun Yat-sen University. His primary research interests include medical image analysis, computer-aided diagnosis, and machine learning. He has conducted research visits at the University of Michigan in Ann Arbor, USA, and the City University of Hong Kong. He has also led one project funded by the Guangdong Provincial Natural Science Foundation, and has published more than 20 papers.

Education

2011.09-2015.06, Sun Yat-sen University, School of Mathematics, Information and Computational Science, BS

2015.08-2020.06, Sun Yat-sen University, School of Computer Science and Engineering, Computational Mathematics, Ph.D

2017.09-2018.08, Visiting Scholar at the University of Michigan, Ann Arbor

2019.09-2020.01, Research Assistant at the Department of Mathematics, City University of Hong Kong

Work Experience

Since 2019.0, lecturer in the Department of Biomedical Engineering, Shantou University

Research

Medical image analysis, computer-aided diagnosis, machine learning.

Current Projects:

Lesion Detection in Bilateral Digital Breast Tomosynthesis Based on Generative Adversarial Networks, Guangdong Provincial Natural Science Foundation, January 1, 2023 - December 31, 2025.

Publications

1. Xiangyuan Ma, Jinlong Wang, Xinpeng Zheng, Zhuangsheng Liu, Wansheng Long, Yaqin Zhang, Jun Wei, Yao Lu. Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks. Physics in Medicine & Biology 2020, 65(10): 105006.

2. Xiangyuan Ma, Jun Wei, Chuan Zhou, Mark A. Helvie, Heang-Ping Chan, Lubomir M. Hadjiiski, Yao Lu. Automated pectoral muscle identification on MLO-view mammograms: Comparison of deep neural network to conventional computer vision. Medical Physics 2019, 46(5): 2103-2114.

3. Xiangyuan Ma, Lubomir M. Hadjiiski, Jun Wei, Heang-Ping Chan, Kenny H. Cha, Richard H. Cohan, Elaine M. Caoili, Ravi Samala, Chuan Zhou, Yao Lu. U-Net based deep learning bladder segmentation in CT urography. Medical Physics 2019, 46(4): 1752-1765.

4. Yue Li, Zilong He, Jiawei Pan, Weixiong Zeng, Jialing Liu, Zhaodong Zeng, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefang Wu, Xiangyuan Ma, Weiguo Chen, Yao Lu. Atypical architectural distortion detection in digital breast tomosynthesis: a computer-aided detection model with adaptive receptive field. Physics in Medicine and Biology 2023, 68(4): 045013.

5. Yue Li, Zilong He, Xiangyuan Ma, Weixiong Zeng, Jialing Liu, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefang Wu, Weiguo Chen, Yao Lu. Architectural distortion detection based on superior–inferior directional context and anatomic prior knowledge in digital breast tomosynthesis. Medical Physics 2022, 49(6): 3749-3768.

6.        Yue Li, Zilong He, Yao Lu, Xiangyuan Ma, Yanhui Guo, Zheng Xie, Genggeng Qin, Weimin Xu, Zeyuan Xu, Weiguo Chen, Haibin Chen. Deep learning of mammary gland distribution for architectural distortion detection in digital breast tomosynthesis. Physics in Medicine & Biology 2021, 66(3): 035028.

7. Yun Chen, Yao Lu, Xiangyuan Ma, Yuesheng Xu. A content-adaptive unstructured grid based regularized CT reconstruction method with a SART-type preconditioned fixed-point proximity algorithm. Inverse Problems 2022, 38(3): 035005.

8. Xiangyuan Ma, Zilong He, Yue Li, Weixiong Zeng, Jiawei Pan, Jialing Liu, Weimin Xu, Zeyuan Xu, Sina Wang, Chanjuan Wen, Hui Zeng, Jiefeng Wu, Zhaodong Zeng, Weiguo Chen, Yao Lu. Multi-view based computer-aided model with anatomical position prior for architectural distortion detection in digital breast tomosynthesis. Vol. 12465. SPIE, 2023.

Teaching

Biomedical Engineering

Medical Imaging Physics

Biomedical Engineering Senior Design

Positions in academic institutions or Professional Affiliations