刘修健
个人基本信息
姓名:刘修健
职称:副教授/硕士生导师
邮箱:liuxj86@mail.sysu.edu.cn
研究方向
专注于泛心血管疾病诊疗中的关键问题,通过跨学科方法结合医学影像分析、计算流体力学以及人工智能等方法,致力于解决疾病辅助诊断与介入治疗中的挑战。
工作经历
(1)2024-10至今,中山大学,生物医学工程学院,副教授
(2)2022-09至2024-09,中山大学,生物医学工程学院,副研究员
(3)2020-08至2022-08,中山大学,生物医学工程学院,博士后
(4)2019-01至2020-02,乐普(北京)医疗器械股份有限公司,项目研发总监
(5)2015-05至2018-12,北京冠生云医疗技术有限公司(乐普子公司),高级工程师
教育经历
(1)2010-09至2015-07,首都医科大学,附属北京安贞医院,生物医学工程专业,博士(硕博连读)
(2)2005-09至2009-07,哈尔滨工程大学,自动化学院,生物医学工程专业,学士
科研项目
(1)国家自然科学基金面上项目,2025至2028,主持
(2)国家自然科学基金青年项目,2022至2024,主持
(3)国家自然科学基金面上项目,2023至2026,参与单位负责人
(4)中国博士后科学基金面上项目,2021至2022,主持
(5)深圳市出站博士后资助项目,2023至2025,主持
近五年学术成果
[1]X. Liu, B. Xie, D. Zhang, H. Zhang, Z. Gao*, V. H. C. de Albuquerque*. Unsupervised physics-informed deep learning for assessing pulmonary artery hemodynamics. Expert Systems with Applications, 2024.
[2]D. Zhang#, X. Liu#, A. Wang, H. Zhang, G. Yang, H. Zhang, Z. Gao*. Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation from Invasive Coronary Imaging. IEEE Transactions on Medical Imaging, 2024.
[3]X. Xue#, D. Deng#, H. Zhang, Z. Gao, P. Zhu, W. K. Hau, Z. Zhang*, X. Liu*. Non-invasive Assessment of Coronary Microvascular Dysfunction Using Vascular Deformation-Based Flow Estimation. IEEE transactions on biomedical engineering, 2024.
[4]A. Wang, H. Zhang, B. Xie, Z. Gao, Y. Dong, C. Peng, X. Liu*, (2024). Main Coronary Flow Calculation With the Assistance of Physiological Side Branch Flow. IEEE Transactions on Biomedical Engineering, 2024.
[5]X. Liu#, G. Guo#, A. Wang, Y. Wang, S. Chen, P. Zhao, Z. Yin, S. Liu, Z. Gao, H. Zhang, L. Zu*. Quantification of functional hemodynamics in aortic valve disease using cardiac computed tomography angiography. Computers in Biology and Medicine, 2024.
[6]W. Zhong, H. Zhang, Z. Gao, W. K. Hau, G. Yang, X. Liu*, L. Xu*. Distraction-aware hierarchical learning for vascular structure segmentation in intravascular ultrasound images. Computerized Medical Imaging and Graphics, 2024.
[7]C. Xu, X. Wu, B. Wang*, J. Chen, Z. Gao, X. Liu*, H. Zhang. Accurate segmentation of liver tumor from multi-modality non-contrast images using a dual-stream multi-level fusion framework. Computerized Medical Imaging and Graphics, 2024.
[8]X. Liu#, S. Li, B. Wang, L. Xu*, Z. Gao*, G. Yang. Motion estimation based on projective information disentanglement for 3D reconstruction of rotational coronary angiography. Computers in Biology and Medicine, 2023.
[9]X. Xue#, X. Liu#*, Z. Gao, R. Wang, L. Xu, D. Ghista, H. Zhang*. Personalized coronary blood flow model based on CT perfusion to non-invasively calculate fractional flow reserve. Computer Methods in Applied Mechanics and Engineering, 2023.
[10]D. Zhang#, X. Liu#, J. Xia, Z. Gao*, H. Zhang*, V. H. C. de Albuquerque. A physics-guided deep learning approach for functional assessment of cardiovascular disease in IoT-based smart health. IEEE Internet of Things Journal, 2023.
[11]H. Liang, Q. Zhang, Y. Gao, G. Chen, Y. Bai, Y. Zhang, K. Cui, Q. Wang, S. Cao, Y. Hou, H. Zhang, D. Ghista, X. Liu*, J. Xiu#. Diagnostic performance of angiography-derived fractional flow reserve analysis based on bifurcation fractal law for assessing hemodynamic significance of coronary stenosis. European Radiology, 2023.
[12]X. Liu#, C. Xu, S. Rao, Y. Zhang, D. Ghista, Z. Gao*, G. Yang. Physiologically personalized coronary blood flow model to improve the estimation of noninvasive fractional flow reserve. Medical Physics, 2022, 封面文章
[13]X. Liu#, T. Feng, W. Liu*, L. Song*, Y. Yuan, W. K. Hau, J. Del Ser, Z. Gao*. Scale mutualized perception for vessel border detection in intravascular ultrasound images. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022.
[14]C. Wu#, X. Liu#, D. Ghista, Y. Yin, H. Zhang*. Effect of plaque compositions on fractional flow reserve in a fluid–structure interaction analysis. Biomechanics and modeling in mechanobiology, 2022.
[15]Z. Chen#, Y. Zhou#, X. Liu#, X. Jiang, T. Wu, D. Ghista, X. Xu*, H Zhang*, Z. Jing*. A personalized pulmonary circulation model to non-invasively calculate fractional flow reserve for artery stenosis detection. IEEE Transactions on Biomedical Engineering, 2021.
其他成果
本人在产业界工作期间,率领团队主导研发的冠状动脉CT血流储备分数计算软件,成功获批国家三类医疗器械注册证。国械注准:20213210837。
招聘与招生
博士后招聘
长期招聘血流动力学和医学图像处理方向的博士后,申请者需具有(或即将拿到)相关专业背景的博士学位。
硕士研究生招生/实习
欢迎有志于科学研究的保研/考研的同学联系我。我们将一起在心血管血流动力学、医学影像分析和计算机视觉等方向挖掘新的科学问题,进行新的探索和尝试。同时欢迎在读硕士来实验室实习(本校外校均可)。
本科生实习
欢迎对科研有浓厚兴趣的,有志于在中山大学继续深造、申请出国攻读硕士/博士学位的同学和我一起进行科学研究。对本科同学的指导以兴趣+学术为导向,主要培养科研兴趣、学术思维和探索能力,并且支持和鼓励本科同学将研究成果发表在学术论文上。表现优异者支持出国参加高水平的学术会议。期待本科1-3年级,具有一定大学数学和编程基础的同学联系我,也欢迎外校的同学来实验室进行交流。