DCP:用于扩散连接的管道工具箱
Weijie Huang1,2,3, Xinyi Dong1, Tengda Zhao1
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, PR China.
Human brain mapping
|February 20, 2024
概括
扩散连接管道 (DCP) 从扩散MRI数据提供自动化大脑结构网络分析. 这个MATLAB工具箱简化了白质连接映射,用于先进的人类大脑连接学研究.
科学领域:
- 神经成像是一种神经成像.
- 计算神经科学是一种神经科学.
- 网络科学 网络科学
背景情况:
- 扩散磁共振成像 (dMRI) 能够通过绘制白质连接来研究大脑结构网络.
- 现有的dMRI处理包和网络分析工具箱对完全自动化的网络分析提出了挑战.
- 结构性大脑连接体的发展需要高效和标准化的分析工作流.
研究的目的:
- 开发一个跨平台的MATLAB工具箱,即扩散连接管道 (DCP),用于自动化大脑结构网络的构建和分析.
- 将已建立的dMRI处理包集成到统一的,用户友好的计算工作流中.
- 验证DCP在复制先前研究结果方面的能力和可靠性.
主要方法:
- 扩散连接管道 (DCP) 作为 MATLAB 工具箱的开发.
- 多个dMRI处理包 (FSL,扩散工具包,SPM,Camino,MRtrix3,MRIcron) 的集成.
- 为非程序员配置处理管道的图形用户界面的实施.
主要成果:
- DCP成功地自动化了大脑结构网络的构建和拓属性的计算.
- 该工具箱证明了其能够重现先前研究的结果,从而验证了其性能.
- 与原始dMRI数据和来自大型数据集 (HCP,英国生物库) 的预处理文件的兼容性得到证实.
结论:
- 扩散连接管道 (DCP) 为白质网络分析提供了标准化,完全自动化的工作流.
- 通过简化复杂的dMRI数据处理,DCP促进了人类大脑连接学研究的进步.
- 局限性包括依赖MATLAB和无法处理基于fixel的指标加权网络.
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