马建华,教授、博士生导师、南医优秀教师,广东省医用放射成像系统工程技术研究中心主任,广州市医用放射成像与检测技术重点实验室主任。
1、学术兼职:中国体视学学会常务理事、中国生物医学工程学会青年委员会副主任委员、中国图象图形学学会理事、中国计量学会CT辐射剂量控制分会委员、广东省生物医学工程学会常务理事、东软医疗系统股份有限公司CT产品研发中心首席科学家、医学成像领域顶级期刊IEEE Transactions on Medical Imaging 期刊副主编、医学物理领域顶级期刊Physics in Medicine and Biology期刊编委。
2、学术论文:发表IEEE Trans./Journal论文和IEEE NSS-MIC/SPIE/Fully3D等清华大学A类重要会议论文125篇(一作/通讯87篇),合计IF:467,H-index:33(Google学术数据)。近5年,一作/通讯期刊论文50篇,包括医学成像领域排名第一期刊IEEE Transactions on Medical Imaging论文12篇(CT成像方向发文量全国首位),IEEE Transactions on Biomedical Engineering论文2篇,IEEE Transactions on Nuclear Science论文1篇,IEEE Transactions on Computational Imaging论文2篇,Physics in Medicine and Biology论文7篇,Medical Physics论文4篇。被引用3888次,引用人含20余位IEEE/AAPM/AIMBE Fellows。
3、科研课题:主持NSFC区域创新基金广东联合基金集成项目(重大)/NSFC区域创新基金辽宁联合基金项目(重点)/NSFC面上项目、国家科技部重点研发计划课题等国家级课题9项、省级课题2项、市级课题2项、广东省实验室重大科研项目1项。
4、科技奖励:2025年度陕西省高等学校科学技术研究优秀成果一等奖(第一完成人)、2022年度“长江学者奖励计划”特聘教授、2021年广东省丁颖科技奖(省科协最高奖)、2019年广东省技术发明奖一等奖(第一完成人)、2015年广东省科学技术奖二等奖(第二完成人)。
[1] D. Li, Z. Bian, S. Li, J. He, D. Zeng, J. Ma*. Noise Characteristics Modeled Unsupervised Network for Robust CT Image Reconstruction, IEEE Trans. Med. Imaging 2022. DOI: 10.1109/TMI.2022.3197400.
[2] J. He, S. Chen, H. Zhang, X. Tao, W. Lin, S. Zhang, D. Zeng, J. Ma*. Downsampled imaging geometric modeling for accurate CT reconstruction via deep learning, IEEE Trans. Med. Imaging 2021, 40(11):2976-2985.
[3] X. Tao, Y. Wang, L. Lin, Z. Hong, J. Ma*. Learning to reconstruct CT images from the VVBP-tensor,IEEE Trans. Med. Imaging 2021, 40(11): 3030-3041.
[4] D. Li, D. Zeng, S. Li, Y. Ge, Z. Bian, J. Huang, J. Ma*. MDM-PCCT: Multiple dynamic modulations for high-Performance spectral PCCT Imaging, IEEE Trans. Med. Imaging 2020, 39(11): 3630-3642.
[5] J. He, Y. Wang, and J. Ma*. Radon inversion via deep learning. IEEE Trans. Med. Imaging 2020, 39(6): 2076-2087.
[6] X. Tao, H. Zhang, Y. Wang, G. Yan, D. Zeng, W. Chen*, and J. Ma*. VVBP-Tensor in the FBP algorithm: its properties and application in low-dose CT reconstruction. IEEE Trans. Med. Imaging 2020, 39(3): 764-776.
[7] D. Zeng#, L. Yao#, Y. Ge, S. Li, Q. Xie, H. Zhang, Z. Bian, Q. Zhao, Y. Li, Z. Xu, D. Meng, and J. Ma*. Full-spectrum-knowledge-aware tensor model for energy-resolved CT iterative reconstruction. IEEE Trans. Med. Imaging 2020, 39(9):2831-2843.
[8] J. He, Y. Yang, Y. Wang, D. Zeng, Z. Bian, H. Zhang, J. Sun, Z. Xu, and J. Ma*. Optimizing a parameterized plug-and-play ADMM for iterative low-dose CT reconstruction. IEEE Trans. Med. Imaging 2019, 38(2): 371-382.
[9] S. Li#, D. Zeng#, J. Peng, Z. Bian, H. Zhang, Q. Xie, Y. Wang, Y. Liao, S. Zhang, J. Huang, D. Meng, Z. Xu, and J. Ma*. An efficient iterative cerebral perfusion CT reconstruction via low-rank tensor decomposition with spatial-temporal total variation regularization. IEEE Trans. Med. Imaging 2019, 38(2): 360-370.
[10] D. Zeng, Q. Xie, W. Cao, J. Lin, H. Zhang, S. Zhang, J. Huang, Z. Bian, D. Meng, Z. Xu, Z. Liang, W. Chen, and J. Ma*. Low-dose dynamic cerebral perfusion computed tomography reconstruction via Kronecker-basis-representation tensor sparsity regularization. IEEE Trans. Med. Imaging 2017, 36(12): 2546-2556.
[11] Q. Xie, D. Zeng, Q. Zhao, D. Meng*, Z. Xu, Z. Liang, and J. Ma*. Robust low-dose CT sinogram preprocessing via exploiting noise-generating mechanism. IEEE Trans. Med. Imaging 2017, 36(12): 2487-2498.