DeepPrep: an accelerated, scalable and robust pipeline for neuroimaging preprocessing empowered by deep learning.

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2025-02-06 DOI:10.1038/s41592-025-02599-1

Jianxun Ren, Ning An, Cong Lin, Youjia Zhang, Zhenyu Sun, Wei Zhang, Shiyi Li, Ning Guo, Weigang Cui, Qingyu Hu, Weiwei Wang, Xuehai Wu, Yinyan Wang, Tao Jiang, Theodore D Satterthwaite, Danhong Wang, Hesheng Liu

引用次数: 0

Abstract

Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing substantial computational challenges. Here we present DeepPrep, a pipeline empowered by deep learning and a workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates tenfold acceleration, scalability and robustness compared to the state-of-the-art pipeline, thereby meeting the scalability requirements of neuroimaging.

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来源期刊

Nature Methods 生物-生化研究方法

CiteScore

58.70

自引率

1.70%

发文量

326

审稿时长

1 months

期刊介绍： Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.