Name: Li Xuesong
Discipline: Computer Science and Technology
Title: Associate Professor, Special Researcher, Doctoral Supervisor
Contact number:
E-mail: lixuesong@bit.edu.cn
Address: Beijing Polytechnic University Center Teaching Building Personal Information
He graduated from Tsinghua University and then joined the School of Computing at Beijing Institute of Technology. At present, he is mainly interested in medical data mining, intelligent medical imaging, goal-guided medical robots and other interdisciplinary research. He has published more than 30 SCI papers and conference papers. Including 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, etc. He has presided over a number of national projects, including the National Natural Science Foundation project, the National Natural Science Foundation Youth Project, the Beijing Natural Science Foundation project, and the sub-project of the key research and development plan of the Ministry of Science and Technology. He is a member of the International Medical Magnetic Resonance Society, the International Human Brain Atlas Society, the Chinese Image Graphics Society, etc., and serves as a reviewer for many top journals (IEEE Trans Image Process, IEEE Transactions on Affective Computing, etc.). Led the team to participate in the hemangioma Detection and Segmentation Challenge organized by MICCAI, a top international medical conference in medical imaging, and won the champion.

Research Direction
1) Convolutional artificial intelligence based on Hypergraph, heterogeneous brain network graph, intelligent medical image, medical data mining
2) Goal-guided navigation robot (surgery, etc.)
3) Ultra-high resolution brain imaging
4) Research on Cerebrovascular digital Intelligent Platform
5) Research on brain-inspired algorithm based on brain connectomics, simulating brain computation

Personal Information
He graduated from Tsinghua University and then joined the School of Computing at Beijing Institute of Technology. At present, he is mainly interested in medical data mining, intelligent medical imaging, goal-guided medical robots and other interdisciplinary research. He has published more than 30 SCI papers and conference papers. Including 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, etc. He has presided over a number of national projects, including the National Natural Science Foundation project, the National Natural Science Foundation Youth Project, the Beijing Natural Science Foundation project, and the sub-project of the key research and development plan of the Ministry of Science and Technology. He is a member of the International Medical Magnetic Resonance Society, the International Human Brain Atlas Society, the Chinese Image Graphics Society, etc., and serves as a reviewer for many top journals (IEEE Trans Image Process, IEEE Transactions on Affective Computing, etc.). Led the team to participate in the hemangioma Detection and Segmentation Challenge organized by MICCAI, a top international medical conference in medical imaging, and won the champion.

Personal Information
He graduated from Tsinghua University and then joined the School of Computing at Beijing Institute of Technology. At present, he is mainly interested in medical data mining, intelligent medical imaging, goal-guided medical robots and other interdisciplinary research. He has published more than 30 SCI papers and conference papers. Including 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, etc. He has presided over a number of national projects, including the National Natural Science Foundation project, the National Natural Science Foundation Youth Project, the Beijing Natural Science Foundation project, and the sub-project of the key research and development plan of the Ministry of Science and Technology. He is a member of the International Medical Magnetic Resonance Society, the International Human Brain Atlas Society, the Chinese Image Graphics Society, etc., and serves as a reviewer for many top journals (IEEE Trans Image Process, IEEE Transactions on Affective Computing, etc.). Led the team to participate in the hemangioma Detection and Segmentation Challenge organized by MICCAI, a top international medical conference in medical imaging, and won the champion.

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.
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