职 称：讲师
E-mail：maxiangyuan@stu.edu.cn
联系地址：广东省汕头市金平区大学路243号汕头大学（邮编：515063）
教育背景
2011.09-2015.06中山大学数学学院，信息与计算科学专业，理学学士
2015.08-2020.06中山大学数据科学与计算机学院，计算数学专业，理学博士
2017.09-2018.08美国密歇根大学安娜堡分校医学院，访问学者
2019.09-2020.01香港城市大学数学系，研究助理
工作背景
2019.09-至今汕头大学工学院，生物医学工程系，理学博士
研究兴趣
医学影像分析、医学计算机辅助诊断、机器学习
科研论文
1. X. Ma, L. Hadjiiski, J. Wei, H-P Chan, K. Cha, R. Cohan, E. Caoili, R. Samala, C. Zhou and Y. Lu. U-Net-based Deep-Learning Bladder Segmentation in CT Urography. Medical Physics, 46(4), 2019, 1752-1765.
2.X. Ma, J. Wei, C. Zhou, M. Helvie, H-P Chan, L. Hadjiiski and Y. Lu. Automated Pectoral Muscle Identification on MLO-view Mammograms: Comparison of Deep Neural Network to Conventional Computer Vision. Medical Physics, 46(5), 2019, 2103-2114.
3.X. Ma, J. Wang, X. Zheng, Z. Liu, W. Long, Y. Zhang, J. Wei and Y. Lu. Automated Fibroglandular Tissue Segmentation in Breast MRI Using Generative Adversarial Networks. Physics in Medicine & Biology, 2020, 65(10): 105006.
4.Y. Li, Z. He, Y. Lu, X. Ma, Y. Guo, Z. Xie, Z. Xu, W. Chen and H. Chen. Deep learning on mammary glands distribution for architectural distortion detection in digital breast tomosynthesis. Physics in Medicine & Biology, 2020.
5.X. Ma, J. Wei, C. Zhou, H-P Chan, L. Hadjiiski and Y. Lu. Fully automated pectoral muscle identification on MLO-view mammograms with deep convolutional neural network. Proc. SPIE 10718, 14th International Workshop on Breast Imaging (IWBI 2018), 1071818.
6.X. Ma, L. Hadjiiski, J. Wei, H-P Chan, K. Cha, R. Cohan, E. Caoili, R. Samala, C. Zhou and Y. Lu. 2D and 3D bladder segmentation using U-Net-based deep-learning. Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis,109500Y:1-6.
7.X. Ma, C. Fisher, J. Wei, M. Helvie, H-P Chan, C. Zhou, L. Hadjiiski and Y. Lu. Multi-path deep learning model for automated mammographic density categorization. Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109502E:1-6.
8.X. Ma, L. Hadjiiski, J. Wei, H-P Chan, K. Cha, R. Cohan, E. Caoili, R. Samala, C. Zhou and Y. Lu. U-Net-Based Deep-Learning Bladder Segmentation in Ct Urography. Radiological Society of North America 2018: Scientific Assembly and Annual Meeting 2018, SSG13-07.
9.Y. Chen, Y. Lu, X. Ma and Y. Xu. Regularized CT reconstruction method on unstructured grid. Proc. of SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97834G: 1-6.
10.Y. Li, Z. Xie, Z. He, X. Ma, Y. Guo, W. Chen and Y. Lu. Architectural distortion detection approach guided by mammary gland spatial pattern in digital breast tomosynthesis. Proc. of SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131417:1-6.
