姓名：李雪松
所在学科：计算机科学与技术
职称：副教授、特别研究员、博士生导师
联系电话：
E-mail：lixuesong@bit.edu.cn
通信地址：北京理工大学中心教学楼个人信息
清华大学博士毕业，之后入职北京理工大学计算学院。目前主要感兴趣的研究方向为医疗数据挖掘、智能医学影像、基于目标引导的医疗机器人等交叉学科领域研究。已经发表30余篇SCI论文和会议论文，包括Medical Image Analysis, Neuroimage, Human Brain Mapping, Magnetic Resonance in Medicine, IEEE Trans, Neurocomputing, Journal of Magnetic Resonance Imaging, American Journal of Geriatric Psychiatry, ISMRM, OHBM, ISBI等。主持多项国家课题，包括国家自然科学基金面上项目、国家自然科学基金青年项目、北京市自然科学基金面上项目、科技部重点研发计划项目子课题等。国际医学磁共振学会会员，国际人类脑图谱学会会员，中国图象图形学会会员等，担任多个顶级期刊审稿人（IEEE Trans Image Process， IEEE Transactions on Affective Computing等）。曾带领团队参加国际医学影像国际医学顶级会议MICCAI组织的血管瘤检测和分割挑战赛获得冠军。

科研方向
1） 基于超图、异构脑网络图卷积人工智能，智能医疗图象，医疗数据挖掘
2） 基于目标引导的导航机器人（手术等领域）
3） 大脑超高分辨率成像
4） 脑血管数字化智能平台研究
5） 脑连接组学为基础的脑启发算法研究, 仿脑计算

个人信息
清华大学博士毕业，之后入职北京理工大学计算学院。目前主要感兴趣的研究方向为医疗数据挖掘、智能医学影像、基于目标引导的医疗机器人等交叉学科领域研究。已经发表30余篇SCI论文和会议论文，包括Medical Image Analysis, Neuroimage, Human Brain Mapping, Magnetic Resonance in Medicine, IEEE Trans, Neurocomputing, Journal of Magnetic Resonance Imaging, American Journal of Geriatric Psychiatry, ISMRM, OHBM, ISBI等。主持多项国家课题，包括国家自然科学基金面上项目、国家自然科学基金青年项目、北京市自然科学基金面上项目、科技部重点研发计划项目子课题等。国际医学磁共振学会会员，国际人类脑图谱学会会员，中国图象图形学会会员等，担任多个顶级期刊审稿人（IEEE Trans Image Process， IEEE Transactions on Affective Computing等）。曾带领团队参加国际医学影像国际医学顶级会议MICCAI组织的血管瘤检测和分割挑战赛获得冠军。

个人信息
清华大学博士毕业，之后入职北京理工大学计算学院。目前主要感兴趣的研究方向为医疗数据挖掘、智能医学影像、基于目标引导的医疗机器人等交叉学科领域研究。已经发表30余篇SCI论文和会议论文，包括Medical Image Analysis, Neuroimage, Human Brain Mapping, Magnetic Resonance in Medicine, IEEE Trans, Neurocomputing, Journal of Magnetic Resonance Imaging, American Journal of Geriatric Psychiatry, ISMRM, OHBM, ISBI等。主持多项国家课题，包括国家自然科学基金面上项目、国家自然科学基金青年项目、北京市自然科学基金面上项目、科技部重点研发计划项目子课题等。国际医学磁共振学会会员，国际人类脑图谱学会会员，中国图象图形学会会员等，担任多个顶级期刊审稿人（IEEE Trans Image Process， IEEE Transactions on Affective Computing等）。曾带领团队参加国际医学影像国际医学顶级会议MICCAI组织的血管瘤检测和分割挑战赛获得冠军。

代表性学术成果
Wu Z, Liao W, Yan C, Zhao M, Liu G, Ma N, Li X. (2023). Deep Learning based MRI Reconstruction with Transformer. Computer Methods and Programs in Biomedicine. 233. 107452. 10.1016/j.cmpb.2023.107452.
Shi G, Zhu Y, Zhang F, Liu W, Yao Y, Li X. (2022). Fusion Learning of Multimodal Neuroimaging with Weighted Graph AutoEncoder. 2467-2473. 10.1109/BIBM.
Zhu Y, Li X, Qiao Y, Shang R, Shi G, Shang Y, Guo H. Widespread plasticity of cognition-related brain networks in single-sided deafness revealed by randomized window-based dynamic functional connectivity. Med Image Anal. 2021 Oct;73:102163. (corresponding author)
Shi G, Li X, Zhu Y, Shang R, Sun Y, Guo H, Sui J. The divided brain: Functional brain asymmetry underlying self-construal. Neuroimage. 2021 Oct 15;240:118382. (corresponding author)
Lv Y, Liao W, Liu W, Chen Z, Li X, A Deep-Learning-Based Framework for Automatic Segmentation and Labelling of Intracranial Artery. IEEE International Symposium on Biomedical Imaging (ISBI) 2023.
LvY, Liao W, Chen Z, Li X, MFR-Net: Multi-Scale Feature Representation Module for 3D Cerebrovascular Segmentation. IEEE International Symposium on Biomedical Imaging 2023.
Liao W, Jiang P, Lv Y, Xue Y, Chen Z, Li X, MCRLe: Multi-Modal Contrastive Representation Learning for Stroke Onset Time Diagnosis. IEEE International Symposium on Biomedical Imaging 2023.
Zhu Y, Li X, Sun Y, Wang H, Guo H and Sui J, Investigating Neural Substrates of Individual Independence and Interdependence Orientations via Efficiency-Based Dynamic Functional Connectivity: A Machine Learning Approach, IEEE Transactions on Cognitive and Developmental Systems , vol. 14, no. 2, pp. 761-771, June 2022. (corresponding author)
Shi G, Zhu Y, Chen Z, Liu J and Li X, Are Non-image Data Really Necessary for Disease Prediction with Graph Convolutional Networks?, IEEE Transactions on Cognitive and Developmental Systems , doi: 10.1109/TCDS.2022.3152791. (corresponding author)
Li X., Steffens, D.C., Potter, G.G., Guo, H., Song, S. and Wang, L. (2017), Decreased between-hemisphere connectivity strength and network efficiency in geriatric depression. Hum. Brain Mapp., 38: 53-67.
Li X, Ma X, Li L, Zhang Z, Zhang X, Tong Y, Wang L, Sen Song, Guo H. Dual-TRACER: High resolution fMRI with constrained evolution reconstruction. Neuroimage. 2018 Jan 1;164:172-182..
Li X, Cao T, Tong Y, Ma X, Niu Z, Guo H. Deep residual network for highly accelerated fMRI reconstruction using variable density spiral trajectory, Neurocomputing,2019.
Qiao Y, Li X, Shen H, Zhang X, Sun Y, Hao W, Guo B, Ni D, Gao Z, Guo H, Shang Y. Downward cross-modal plasticity in single-sided deafness, Neuroimage,2019 (co-first author).
Li X, Qiao Y, Shen H, Niu Z, Shang Y, Guo H. Topological reorganization after partial auditory deprivation---a structural connectivity study in single-sided deafness, Hearing Research, 2019, 380: 75-83.
Su Z, Jia Y, Liao W, Lv Y, Dou J, Sun Z, Li X (2021) 3D Attention U-Net with Pretraining: A Solution to CADA-Aneurysm Segmentation Challenge. In: Hennemuth A., Goubergrits L., Ivantsits M., Kuhnigk JM. (eds) Cerebral Aneurysm Detection. CADA 2020. Lecture Notes in Computer Science, Springer, Cham. (corresponding author)
Jia Y, Liao W, Lv Y, Su Z, Dou J, Sun Z, Li X. (2021) Detect and Identify Aneurysms Based on Adjusted 3D Attention UNet. In: Hennemuth A., Goubergrits L., Ivantsits M., Kuhnigk JM. (eds) Cerebral Aneurysm Detection. CADA 2020. Lecture Notes in Computer Science, Springer, Cham (corresponding author)
Zhang Q, Su P, Chen Z, Liao Y, Chen S, Guo R, Qi H, Li X, Zhang X... Deep learning–based MR fingerprinting ASL ReconStruction (DeepMARS). Magnetic Resonance in Medicine, 2020.
Zhang X, Li X, Steffens D, Guo H, Wang L. Dynamic changes in thalamic connectivity following stress and its association with future depression severity. Brain and Behavior, 2019
Shi D, Pan Z, Li X, Guo H, Zheng Q. Diffusion coefficient orientation distribution function for diffusion magnetic resonance imaging. Journal of Neuroscience Methods, 2021.
Yan T, Wang Y, Weng Z, Du W, Liu T, Chen D, Li X, Wu J and Han Y. Early-Stage Identification and Pathological Development of Alzheimer’s Disease Using Multimodal MRI. Journal of Alzheimer’s Disease,2019, 68:1013–1027.
Wei H, Hu Z, Xiong Y, He L, Ma Y, Guo H, Li X. Analysis of Structural Connectivity using Certain Nuclei as Seeds in Patients with Parkinson’s Disease. International Society for Magnetic Resonance in Medicine,2018.
Shi, D, Li, S, Chen L, Li X, Guo H, Zheng Q. (2022). General orientation transform for the estimation of fiber orientations in white matter tissues. Magnetic Resonance in Medicine. 88. 10.1002/mrm.29256.
Xiong, Y, Ji, L, He L, Chen L, Zhang X, Chen Z, Li X, Zhao H... (2021). Effects of Levodopa Therapy on Cerebral Arteries and Perfusion in Parkinson's Disease Patients. Journal of Magnetic Resonance Imaging. 55. 10.1002/jmri.27903.
所获奖励