脑血管系统是维持大脑正常代谢与功能的高度互联网络。获取并解析毛细血管分辨率的全脑血管图谱，对于理解脑疾病（如阿尔茨海默病、中风等）的发病机理具有至关重要的作用。本课题组致力于利用先进的介观光学成像技术（fMOST），融合人工智与并行计算，解决TB级海量脑血管图像的“看、分、算”难题。主要包括：

人工智能驱动的复杂脉管分割与拓扑重建：研究基于深度学习的血管自动重建技术，重点突破复杂背景下的拓扑结构保持算法，实现跨尺度脉管系统的精准自动化重建。

大规模复杂网络的高效可视化与沉浸式交互：研究三维图像渲染技术，TB级超大规模脉管网络的的沉浸式交互与可视化。

高精度数字脑血管图谱构建与定量表征：绘制毛细血管分辨率的小鼠全脑动静脉图谱，多维度定量分析血管形态特征，实现全脑尺度的数字化表征。

脑微循环网络时空演变规律研究：结合阿尔茨海默病等疾病模型，解析微循环网络的时空演变规律，为疾病、发育等提供支撑。

完整器官全尺度脉管系统数字化重建：将全脑重建技术体系迁移至肾脏、肝脏、肺等全身器官，实现复杂组织结构的高精度解析。

每年招收1-2名硕士研究生，欢迎对此方向感兴趣的同学与我联系。

代表性成果(#Co-first author;*Corresponding author)

[1] Li Yuxin, Zhang Qianlong, Zhou Hang, An Yang, Li Junhuai, Li Xiangning, Zhou Hongfang, Li Anan* Deep learning-based interactive segmentation of three-dimensional blood vessel images. Biomedical Signal Processing and Control, 2025, 104: 107507.

[2] Feng Zhao, Li Xiangning, Luo Yue, Liu Xin, Long Ben, Jiang Tao, Jia Xueyan, Chen Xiaowei, Luo Jie, Chai Xiaokang, Wang Zhen, Ren Miao, Lu Xin, Yao Gang, Zhao Mengting, Li Yuxin, Liu Zhixiang, Ni Hong, Dou Chuhao, Bao Shengda, Yang Shicheng, Zhang Zoutao, Zhou Jiandong, Cai Lingyi, Zhang Qi, Tudi Ayizuohere, Tan Chaozhen, Xu Zhengchao, Chen Siqi, Ding Wenxiang, Shi Wenjuan, Li Anan, Dong Hong-wei*, Gong Hui*, Luo Qingming*. A mouse brain stereotaxic topographic atlas with isotropic 1-μm resolution. Nature, 2025, 645: 448–456.

[3] Li Yuxin, Cao Jia, Zhang Qianlong, Li Junhuai, Li Xiangning, Zhou Hongfang, Li Anan, Jiang Tao*. Precise reconstruction of the entire mouse kidney at cellular resolution. Biomedical Optics Express, 2024, 15(3): 1474-1485.

[4] Li Yuxin*, Liu Xuhua, Jia Xueyan, Jiang Tao, Wu Jianghao, Zhang Qianlong, Li Junhuai, Li Xiangning, Li Anan*. A high-performance deep-learning-based pipeline for whole-brain vasculature segmentation at the capillary resolution. Bioinformatics, 2023, 39(4): btad145.

[5] Zhou Hang, Li Yuxin*, Chen Bolun, Yang Hao, Zou Maoyang, Wen Wu, Ma Yayu, Chen Min. Registration-free 3D super-resolution generative deep-learning network for fluorescence microscopy imaging. Optics Letters, 2023, 48(23): 6300-6303.

[6] Li Yuxin, Ren Tong, Li Junhuai, Wang Huaijun, Li Xiangning, Li Anan*. VBNet: An end-to-end 3D neural network for vessel bifurcation point detection in mesoscopic brain images. Computer Methods and Programs in Biomedicine, 2022, 214: 106567.

[7] Li Yuxin, Gong Hui, Yang Xiaoquan, Yuan Jing, Jiang Tao, Li Xiangning, Sun Qingtao, Zhu Dan, Wang Zhenyu, Luo Qingming, Li Anan*. TDat: an efficient platform for processing petabyte-scale whole-brain volumetric images. Frontiers in neural circuits, 2017, 11: 51.

[8] Gong Hui#, Xu Dongli#, Yuan Jing, Li Xiangning, Guo Congdi, Peng Jie, Li Yuxin, Schwarz Lindsay A., Li Anan, Hu Bihe, Xiong Benyi, Sun Qingtao, Zhang Yalun, Liu Jiepeng, Zhong Qiuyuan, Xu Tonghui, Zeng Shaoqun, Luo Qingming*. High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. Nature Communications, 2016, 7: 12142.

[9] Quan Tingwei, Zhou Hang, Li Jing, Li Shiwei, Li Anan, Li Yuxin, Lv Xiaohua, Luo Qingming, Gong Hui*, Zeng Shaoqun*. NeuroGPS-Tree: automatic reconstruction of large-scale neuronal populations with dense neurites. Nature Methods, 2016, 13(1): 51-54.

[10] 荧光显微光学切片断层成像关键技术及应用, 2020-2021年度“黄家驷生物医学工程奖”技术发明一等奖, 骆清铭; 龚辉; 李安安; 袁菁; 李向宁; 江涛; 李宇昕; 丰钊