刘琮

一、个人简介

   刘琮，男，1982年，博士，副教授。

二、培养方向

运筹优化的医疗应用

三、主要研究内容

研究方向：统计机器学习、运筹优化、计算机视觉等。

研究内容：基于人工智能技术的医学物理的领域创新与优化：利用人工智能技术和运筹优化，如机器学习、自然语言处理、计算机视觉等，为医疗客户提供个性化、智能化、高效化的服务。

四、学术或社会兼职

中国医学物理学会 英国物理学会(IOP)

五、主要学术或实践成果

Jin, X., Zheng, X., Liu, C., & Xie, C. (2019). Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics. European Radiology, 29, 6080–6088.

Liu, C., Lu, Z., Ma, L., Wang, L., Jin, X., & Si, W. (2019). A modality conversion approach to MV-DRs and KV-DRRs registration using information bottlenecked conditional generative adversarial network. Medical Physics, 46(10), 4575–4587.

Liu, C., Ma, L., Lu, Z., Jin, X., & Xu, J. (2019). Multimodal medical image registration via common representations learning and differentiable geometric constraints. Electronics Letters, 55(6), 316–318.

Liu, C., Ni, X., Jin, X., & Si, W. (2021). NeuralDAO: Incorporating neural network generated dose into direct aperture optimization for end-to-end IMRT planning. Medical Physics, 48(10), 5624–5638.

Liu, C., Wang, Q., Si, W., & Ni, X. (2022). NuTracker: a coordinate-based neural network representation of lung motion for intrafraction tumor tracking with various surrogates in radiotherapy. Physics in Medicine & Biology, 68(1), 015006.

Sun, J., Liu, C., Li, C., Lu, Z., He, M., Gao, L., Lin, T., Sui, J., Xie, K., & Ni, X. (2021). CrossModalNet: exploiting quality preoperative images for multimodal image registration. Physics in Medicine & Biology, 66(17), 175002.