In order to support efficient processing, data must be formatted according to standards that are prevalent in the field and widely supported among actively developed analysis tools.The Brain Imaging Data Structure (BIDS) (Gorgolewski et al., 2016) is an open standard designed for computational accessibility, operator legibility, and a wide and easily extendable scope of modalities -and is consequently used by numerous analysis and processing tools as the preferred input format in many fields of neuroscience.HeuDiConv (Heuristic DICOM Converter) enables flexible and efficient conversion of spatially reconstructed neuroimaging data from the DICOM format (quasi-ubiquitous in biomedical image acquisition systems, particularly in clinical settings) to BIDS, as well as other file layouts.HeuDiConv provides a multi-stage operator input workflow (discovery, manual tuning, conversion) where a manual tuning step is optional and the entire conversion can thus be seamlessly integrated into a data processing pipeline.HeuDiConv is written in Python, and supports the DICOM specification for input
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Halchenko et al. (2024) studied this question.
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