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基于弥散磁共振成像的全自动三维白质束分割

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

机构信息

Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode, Urayasu, Chiba, 279-0013, Japan.

Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.

出版信息

Anat Sci Int. 2023 Jul;98(3):318-336. doi: 10.1007/s12565-023-00715-9. Epub 2023 Apr 5.

Abstract

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.

摘要

使用弥散磁共振成像纤维束追踪对白质束进行分割,能够对各个白质束进行三维详细评估,在研究人类大脑解剖结构、功能、发育和疾病方面发挥着关键作用。结合感兴趣区的包含和排除来手动提取轨迹线,可以被认为是从全脑纤维束追踪中提取白质束的当前金标准。然而,这是一个耗时且依赖于操作者的过程,其可重复性有限。已经提出了几种使用不同策略来重建白质束的自动化方法,以解决时间、劳动力和可重复性的问题。在这篇综述中,我们讨论了一些经过充分验证的方法,这些方法通过端到端的流水线自动对白质束进行分割,包括基于解剖结构的跟踪受限(TRACULA)、自动纤维定量和 TractSeg。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb95/10256641/4ff89545e528/12565_2023_715_Fig1_HTML.jpg

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