fMRIPrep: a robust preprocessing pipeline for functional MRI
fMRIPrep: a robust preprocessing pipeline for functional MRI
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DOI：
10.1038/s41592-018-0235-4
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发表时间：
2019-01-01
期刊：
影响因子：
48
通讯作者：
Gorgolewski, Krzysztof J.
中科院分区：
文献类型：
--
作者：
Esteban, Oscar;Markiewicz, Christopher J.;Gorgolewski, Krzysztof J.
功能性磁共振成像（fMRI）的预处理包括许多步骤，在统计分析之前对数据进行清理和标准化。一般来说，研究人员会为每个数据集创建临时的预处理工作流，并建立在大量可用工具的基础上。这些工作流程的复杂性随着采集和处理的快速发展而滚雪球。我们介绍fMRIPrep，分析不可知的工具，解决了强大的和可重复的fMRI数据预处理的挑战。fMRIPrep自动调整最佳工作流程以适应几乎任何数据集的特性，确保高质量的预处理，而无需手动干预。通过将视觉评估检查点引入到软件测试的迭代集成框架中，我们证明了fMRIPrep在不同的fMRI数据收集上稳健地产生高质量的结果。此外，fMRIPrep引入的不受控制的空间平滑度比常用的预处理工具所观察到的要少。fMRIPrep为神经科学家提供了一个易于使用和透明的预处理工作流程，可以帮助确保推理的有效性和结果的可解释性。
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances in acquisition and processing. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for fMRI data. fMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing without manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection. Additionally, fMRIPrep introduces less uncontrolled spatial smoothness than observed with commonly used preprocessing tools. fMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessing workflow, which can help ensure the validity of inference and the interpretability of results.