Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging

被引:8
|
作者
Andica, Christina [1 ,2 ]
Kamagata, Koji [2 ]
Aoki, Shigeki [1 ,2 ]
机构
[1] Juntendo Univ, Fac Hlth Data Sci, 6-8-1 Hinode, Urayasu, Chiba 2790013, Japan
[2] Juntendo Univ, Dept Radiol, Grad Sch Med, 2-1-1 Hongo,Bunkyo Ku, Tokyo 1138421, Japan
基金
日本学术振兴会;
关键词
Automatic; Diffusion magnetic resonance imaging; Tractography; White matter; FIBER TRACTOGRAPHY; PARKINSON DISEASE; WATER DIFFUSION; MULTI-TISSUE; MRI; CONNECTIVITY; ANATOMY; BRAIN; MICROSTRUCTURE; QUANTIFICATION;
D O I
10.1007/s12565-023-00715-9
中图分类号
R602 [外科病理学、解剖学]; R32 [人体形态学];
学科分类号
100101 ;
摘要
White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.
引用
收藏
页码:318 / 336
页数:19
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