BIDSconvertR

DOI BIDS Github License: GPL v3

BIDSconvertR The hexagonal sticker was made using the iconspackage and based on the MRI svg graphics provided by Flaticon and mavadee FlaticonLink.
Table of contents
  1. BIDSconvertR
    1. Aim
    2. Features
    3. Workflow visualization
  2. How to cite:
    1. Milestones / To-Do’s

Aim

BIDSconvertR aims to provide a workflow that can:


Features

  • continuous application
    • lazy processing of already existing files
    • easy application during data collection in ongoing studies
  • user-friendliness (minimal terminal interaction required)
    • user dialog with message boxes guiding the users through the workflow
    • Shiny App (GUI) for sequence editing and data inspection
  • file cleaning
    • Renaming of subject-IDs or session-IDs with regular expressions.
    • Renaming of session-IDs
  • BIDS validation
    • verification (color-coded) of sequence-IDs (comparing the entered sequence-IDs to regular expressions according to BIDS)
    • implemented validation with BIDS-Validator (Website/Docker)
  • quality control
    • user-friendly (papayaWidget image viewer) for BIDS datasets
  • pseudonymized BIDS output (only metadata)
    • all potentially identifiable metadata was removed from images and JSONs

Only the metadata contained within the BIDS folder is free of potentially identifiable information. Follow the legal terms when sharing your dataset and consider additional defacing, pseudonymization, or both.


Workflow visualization

Workflow


How to cite:

Wulms N, Eppe S, Dehghan‑Nayyeri M, Streeter A, Bonberg N, Berger K, Sundermann B, Minnerup H. (2023). The R package for DICOM to brain imaging data structure conversion Nature Scientific Data. 2023 Oct 04. doi: 10.1038/s41597‑023‑02583‑4 https://doi.org/10.1038/s41597-023-02583-4

Wulms, Niklas. (2023). BIDSconvertR. Zenodo. https://doi.org/10.5281/ZENODO.5878407


Milestones / To-Do’s

  • create Docker container
  • move image viewer into separate package
  • adapt code to CRAN requirements