北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2023, Vol. 46 ›› Issue (6): 1-0.

• 智慧医疗 •    下一篇

基于人工智能的白质纤维束分割方法与研究进展

宗芳荣,张迪,魏婧怡,王怡然,刘勇   

  1. 北京邮电大学

  • 收稿日期:2023-03-01 修回日期:2023-05-18 出版日期:2023-12-28 发布日期:2023-12-29
  • 通讯作者: 刘勇 E-mail:yongliu@bupt.edu.cn

Methods and Research Progress of AI-based White Matter Tract Segmentation

  • Received:2023-03-01 Revised:2023-05-18 Online:2023-12-28 Published:2023-12-29

摘要: 基于扩散磁共振成像数据进行纤维追踪可得到白质纤维轨迹,根据纤维特征将其分割成不同簇束有助于临床针对性分析和精确诊疗。首先介绍大脑白质纤维学和分割原理;然后归纳基于体素和基于纤维流线的方法,重点介绍不同人工智能技术并设计实验以展示分割结果;最后梳理纤维束分割方法面临的挑战,探讨该领域的研究趋势,展望人工智能技术应用的发展前景,为亚健康人和疾病患者的神经科学研究提供全面的方法总结与诊断支持。

关键词: 扩散磁共振成像, 白质纤维束, 分割, 人工智能, 脑科学

Abstract: Diffusion magnetic resonance imaging allows mapping white matter fiber tracts via a process called tractography. Segmentation of white matter tracts according to fiber characteristics can assist statistical analysis and precision medicine. In this paper, we first introduce the principles of white matter tractography and segmentation. Then, we categorize state-of-the-art segmentation methods into voxel-based and fiber-based categories. Moreover, various artificial intelligence algorithms on segmentation are summarized and concluded, and an experiment is conducted to show the segmentation results. Finally, we discuss the challenges and research trends, and forecast the progress prospect of artificial intelligence in white matter tract segmentation. In summary, the review  provides a comprehensive methodological summary and diagnostic support for downstream neuroscience research in sub-healthy individuals and patients.

Key words: diffusion magnetic resonance imaging, white matter tract, segmentation, artificial intelligence, brain science

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