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，B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（AD）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。

跨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、肝脏等全身器官，实现复杂组织结构（如肾小球、肾元等）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)

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

Feng Zhao, …… Li Yuxin, ……, Dong Hong-wei*, Gong Hui*, Luo Qingming*.A mouse brain stereotaxic topographic atlas with isotropic 1-μm resolution. Nature, 2025, 645: 448–456.

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

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

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.

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.

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.

Quan Tingwei, ……, Li Yuxin, ……, Gong Hui*, Zeng Shaoqun*. NeuroGPS-Tree: automatic reconstruction of large-scale neuronal populations with dense neurites. Nature Methods, 2016, 13(1): 51-54.

Gong Hui#, Xu Dongli#, ……, Li Yuxin,……, Luo Qingming*.High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. NatureCommunications, 2016, 7: 12142.

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