Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.
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DOI：
10.3389/fninf.2011.00013
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发表时间：
2011
影响因子：
3.5
通讯作者：
Ghosh SS
中科院分区：
文献类型：
--
作者：
Gorgolewski K;Burns CD;Madison C;Clark D;Halchenko YO;Waskom ML;Ghosh SS
当前的神经影像软件为用户提供了一个绝佳的机会，使其能够以不同的方式并基于不同的潜在假设来分析数据。一些复杂的软件包（例如AFNI、BrainVoyager、FSL、FreeSurfer、Nipy、R、SPM）被用于处理和分析大量且通常多样（高度多维）的数据。然而，这种专门应用的异构集合产生了几个问题，阻碍了神经影像分析方法的可重复性、高效性和最佳使用：（1）无法统一获取神经影像分析软件和使用信息；（2）没有用于比较算法开发和传播的框架；（3）实验室人员的流动往往限制了方法的连续性，而且培训新人员需要时间；（4）神经影像软件包没有解决计算效率问题；（5）期刊文章中的方法部分不足以重现结果。为了解决这些问题，我们推出了Nipype（Python中的神经影像：管道和接口；），这是一个开源的、由社区开发的软件包和可脚本化的库。Nipype通过为现有神经影像软件提供具有统一使用语义的接口，并利用工作流促进这些软件包之间的交互，从而解决了这些问题。Nipype提供了一个环境，鼓励对算法进行交互式探索，简化软件包内部和之间工作流的设计，允许快速进行算法的比较开发，并降低使用不同软件包所需的学习曲线。Nipype支持在多核机器和集群上进行本地和远程执行，无需额外的脚本。Nipype采用伯克利软件发行版许可，允许任何人无限制地使用。一种开放的、由社区驱动的开发理念使该软件能够快速适应并满足不断发展的神经影像社区的各种需求，特别是在对可重复性研究的需求不断增加的背景下。
Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; ), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for reproducible research.