Literature DB >> 36064140

Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets.

Sydney Covitz1, Tinashe M Tapera1, Azeez Adebimpe1, Aaron F Alexander-Bloch2, Maxwell A Bertolero1, Eric Feczko3, Alexandre R Franco4, Raquel E Gur5, Ruben C Gur5, Timothy Hendrickson6, Audrey Houghton3, Kahini Mehta1, Kristin Murtha1, Anders J Perrone3, Tim Robert-Fitzgerald7, Jenna M Schabdach2, Russell T Shinohara7, Jacob W Vogel1, Chenying Zhao8, Damien A Fair3, Michael P Milham9, Matthew Cieslak1, Theodore D Satterthwaite10.   

Abstract

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled "Curation of BIDS" (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad--a version control software package for data--as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images' metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.
Copyright © 2022. Published by Elsevier Inc.

Entities:  

Keywords:  BIDS; Brain; Curation; Heterogeneity; MRI; Metadata; Neuroimaging; Software; Validation; Version control

Year:  2022        PMID: 36064140     DOI: 10.1016/j.neuroimage.2022.119609

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   7.400


  1 in total

1.  An analysis-ready and quality controlled resource for pediatric brain white-matter research.

Authors:  Adam Richie-Halford; Matthew Cieslak; Lei Ai; Sendy Caffarra; Sydney Covitz; Alexandre R Franco; Iliana I Karipidis; John Kruper; Michael Milham; Bárbara Avelar-Pereira; Ethan Roy; Valerie J Sydnor; Jason D Yeatman; Theodore D Satterthwaite; Ariel Rokem
Journal:  Sci Data       Date:  2022-10-12       Impact factor: 8.501

  1 in total

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