[en] The "Brain Imaging Data Structure" (BIDS) has become a widely adopted standard for organizing and sharing neuroimaging datasets of various modalities. However, converting raw brain imaging data into BIDS framework remains a complex and time-consuming task. BIDSme is a semi-automated tool developed to streamline this conversion process, but until recently, it lacked the portability and accessibility needed for widespread adoption. This paper presents the containerization of BIDSme using Docker and Docker Compose, improving usability, reproducibility, and integration into existing platforms like Neurodesk. It also details the design choices, iterative refinements, and validation process that led to a flexible, lightweight, and user-friendly containerized application.
Research Center/Unit :
GIGA CRC In vivo Imaging-Neuroimaging, data acquisition and processing - ULiège
Disciplines :
Computer science Engineering, computing & technology: Multidisciplinary, general & others Neurology Public health, health care sciences & services
Author, co-author :
Spitz, Bradley; Université de Strasbourg, France > Télécom Physique Strasbourg
Jacquemin, Antoine ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore)
Beliy, Nikita ; Université de Liège - ULiège > Département de Psychologie > Neuropsychologie de l'adulte
Phillips, Christophe ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore)
Language :
English
Title :
Containerizing BIDSme : A Reproducible Tool for BIDS Conversion