Signal Processing Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
PLoS One. 2012;7(12):e48121. doi: 10.1371/journal.pone.0048121. Epub 2012 Dec 18.
Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.
研究人员在使用扩散磁共振成像(dMRI)进行全局连通性分析的领域,可以依靠各种软件包来处理他们的数据,这些方法从重建局部体素内轴突结构到估计基础纤维束的轨迹都有。然而,每个软件包通常都是特定于任务的,并且使用自己的约定和文件格式。在本文中,我们介绍了 Connectome Mapper,这是一个软件管道,旨在帮助研究人员完成组织、处理和分析扩散 MRI 数据的繁琐过程,以进行全局大脑连通性分析。我们的管道是用 Python 编写的,并在 www.cmtk.org 上作为开源免费提供。