Benefits

By using this standard you will benefit in the following ways:

• It will be easy for another researcher to work on your data. To understand the organization of the files and their format you will only need to refer them to this document. This is especially important if you are running your own lab and anticipate more than one person working on the same data over time. By using BIDS you will save time trying to understand and reuse data acquired by a graduate student or postdoc that has already left the lab.
• There is a growing number of data analysis software packages that can understand data organized according to BIDS.
• Databases such as OpenNeuro.org, LORIS, COINS, XNAT, SciTran, and others will accept and export datasets organized according to BIDS. If you ever plan to share your data publicly (nowadays some journals require this) you can speed up the curation process by using BIDS.
• There are validation tools (also available online) that can check your dataset integrity and let you easily spot missing values.

Converters

MRI and PET converters

Name	Expected input	Language	Distribution	Comment	Updated
bidsify	DICOM PAR/REC	Python		Tool to convert source MRI datasets to BIDS-compatible datasets.
bidskit	DICOM	Python		Utility functions for working with DICOM and BIDS neuroimaging data.
BMAT	DICOM	Python
Data2Bids	not DICOM	Python		Converts MRI files from extension supported by nibabel into NIfTI and convert them to BIDS
Dcm2Bids	DICOM	Python		converts DICOM files using dcm2niix into BIDS
HeuDiConv	DICOM	Python		A flexible DICOM converter for organizing brain imaging data into structured directory layouts
OpenfMRI2BIDS				Convert OpenfMRI dataset to BIDS
ReproIn		Python		HeuDiConv-based turnkey solution: a setup for automatic generation of shareable, version-controlled BIDS datasets from MR scanners.
XNAT2BIDS		shell		Simple xnat pipeline to convert DICOM scans to BIDS-compatible output (nii+json).
Horos (Osirix) export plugin		objective C		Horos plugin for BIDS output.
BIDScoin	DICOM PAR/REC physiological PET Nifti	Python		BIDScoin converts your source-level neuroimaging data to BIDS
BIDSme	DICOM Nifti Brain Vision	Python
BrkRaw	Bruker MRI scanner data	Python		For a preclinical Bruker MRI scanner
Clinica	ADNI AIBL NIFD OASIS OASIS-3	Python
niix2bids	Nifti converted from DICOM using dcm2niix	Python		Use this package as a command line to organize your Nifti dataset into BIDS.
dac2bids	DICOM	Python		Create a BIDS structure for a DICOM folder.
Autobids	DICOM			Automated Dicom to BIDS and pipelines using compute canada. From the Center for Functional and Metabolic Mapping (CFMM) at Western’s Robarts Research Institute.
PET2BIDS	DICOM ECAT	MATLAB Python		Helps you convert your PET data! raw PET scanner files (for example ecat, dicom) and additional side file like excel sheets.
Explore ASL	DICOM Nifti	MATLAB		Convert DICOM and NIFTI data to the ASL-BIDS format.
SAMRI	Bruker ParaVision NIfTI	Python shell		Full stack Small Animal MRI data analysis package, including the `bru2bids` repositing pipeline, which can convert Bruker archives to the BIDS format. From the ETH and University of Zurich, with collaboration from MIT and Dartmouth College.
BIDSconvertR	DICOM	R		The BIDSconvertR R package provides a user-friendly workflow with graphical user interfaces. It consists of the following steps: (i) convert DICOM data to NIfTI data using dcm2niix (ii) structure this data according to the BIDS specification (iii) provide the papayaWidget viewer for inspecting the images
ezBIDS	DICOM NIfTI/JSON events (tsv, csv, txt, out, xlsx)	Vue TypeScript Javascript Python shell		A web-based BIDS conversion tool with four unique features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) Semi-automated inference and guidance for adherence to BIDS. (4) Multiple data management options, including download BIDS data to local system, or transfer to OpenNeuro.org or to brainlife.io.
mercure-dcm2bids	DICOM	Python		A containerized app that can be used to perform BIDS conversion of DICOM studies sent directly to mercure from a scanner or PACS. mercure is an open-source DICOM orchestration platform that can integrate containerized apps into clinical workflows. It has a graphical user interface making it easy to setup and manage BIDS configurations for multiple protocols. The Dcm2Bids tool is used for conversion.

EEG, MEG, iEEG converters

Name	Expected input	Language	Distribution	Comment	Updated
BIDSme	DICOM Nifti Brain Vision	Python
MNE-BIDS	raw MEG for BIDS conversion raw EEG for BIDS conversion raw iEEG for BIDS conversion raw NIRS for BIDS conversion BIDS dataset for reading	Python		MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
EEGLAB	EDF BDF Brain Vision Exchange Format EEGLAB .set files	MATLAB		See plugins
FieldTrip - data2bids	any EEG or MEG file format NBS Presentation logfiles DICOM nifti	MATLAB
Biscuit		Python		GUI for easy MEG to BIDS conversion
sovabids		Python		A Python package for the automatic conversion of EEG datasets to the BIDS standard, with a focus on making the most out of metadata.
EEG2BIDS		Javascript Python		A tool for converting raw EEG and iEEG data into the BIDS standard data structure, prepared for LORIS (Longitudinal Online Research and Imaging System).

'From BIDS' converters

Converters that take a BIDS dataset as input to convert it into something else. Not mentioned here are the many software that can import a BIDS data as data structure they are more familiar with.

Name	Expected input	Language	Distribution	Comment	Updated
BIDS2ISATab	BIDS	Python		Extract ISA-Tab compatible metadata from BIDS
BIDSto3col	BIDS	shell Python		Reads BidsTSV and then creates 3 column event files, one per event type if a "trial_type" column is found.
BIDS2NDA	BIDS	Python		Extract NIHM Data Archive compatible metadata from BIDS
bids2xar - for XNAT import	BIDS	Python		Convert BIDS data set into XNAT XAR bundles
BIDS2NIDM	BIDS	Python		This program will convert a NIDM-Experiment RDF document to a BIDS dataset.
AFNI BIDS-tools	BIDS	shell Python		ARCHIVED - Scripts, tools, and documents on creating, parsing, and working with BIDS-structured data sets.

Physiological data converters

Name	Expected input	Language	Distribution	Comment	Updated
BIDScoin	DICOM PAR/REC physiological PET	Python		BIDScoin converts your source-level neuroimaging data to BIDS
phys2bids	Acqknowledge Labchart GE physiological files	Python		Python3 library to format physiological files in BIDS.
bidsphysio	CMRR, AcqKnowledge, Siemens PMU	Python		Converts physio data (CMRR, AcqKnowledge, Siemens PMU) to BIDS physiological recording

Miscellaneous

Not exactly BIDS converters but are common tools that can used by other BIDS converters.

Name	Expected input	Language	Distribution	Comment	Updated
convert-eprime	E-Prime log files	Python		Python functions to convert E-Prime files to csvs. Not currently being developed.
DCM2NIIx		C++ (compiled versions available from <ahref="https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPage">NITRC</a>)		dcm2nii DICOM to NIfTI converter
DICM2NII	DICOM	MATLAB		dcm2nii DICOM to NIfTI converter
sim2bids	network and coordinate files expected_input: CSV/TSV/DAT/Numpy arrays/HDF5, zip folders, and code files in MATLAB/Python/R	Python		GUI to easily convert simulation results to BIDS format, according to BEP 34 .

Software currently supporting BIDS:

• BIDS Apps (a growing set of portable containerized data processing pipelines that understand BIDS datasets)

A description of how to build containerized apps supporting BIDS inputs can be found in the paper published in PLOS Computational Biology.

Other Tools

• babs:

  BIDS App Bootstrap (BABS) is a reproducible, generalizable, and scalable Python package for BIDS App analysis of large datasets. It uses DataLad and adopts FAIRly big framework.

• BIDSHandler:

  Python module allowing complete manipulation of BIDS data

• bids-cfood:

  a module to handle BIDS dataset for the caosDB data crawler

• bids2cite:

  package to interactively update dataset_description.json and generate citation files (for example datacite.yml) for BIDS datasets.

• bids-matlab:

  MATLAB/Octave tools to interact with datasets conforming to the BIDS format

• BIDS-pydantic:

  Pulls a specified version of the BIDS schema and creates corresponding Pydantic models, which will provide BIDS data validation using Python type annotations. See also BIDS-pydantic-models.

• bidser:

  Working with Brain Imaging Data Structure in R

• bids stats model:

  Validate BIDS statistical model. To learn more the BIDS stats model website

• Hierarchical Event Descriptors (HED) online tools:

  Online tools for annotation, validation, summary, and assembly of event file contents and annotations.

• Hierarchical Event Descriptors (HED) python tools:

  HED libraries supporting schema development as well as annotation, validation, and analysis.

• Brainstorm:

  MEG/EEG analysis package

• clpipe:

  streamlined processing pipeline for MRI data centered around BIDS

• cuBIDS:

  a Python package designed to facilitate reproducible curation of neuroimaging BIDS datasets

• File mapper:

  An easy tool to copy/move/symlink files from one directory to the other! Can be used to “convert” dataset to be BIDS compliant.

• GUI dataset description generator:

  GUI form that generates dataset_description.json

• Lead-DBS:

  A toolbox facilitating Deep Brain Stimulation electrode reconstructions and computer simulations supports BIDS conversion and ingestion of BIDS datasets.

• mne-bids:

  collection of tools for converting magnetoencephalography (MEG) data into BIDS format, as well as some helper functions for creating the folders and metadata needed for a BIDS dataset.

• neurobagel annotate:

  This tool allows you to create a machine readable data dictionary in .json format for a tabular phenotypic file in .tsv format (“Data table”).

• neurobagel query:

  Neurobagel’s query tool is a web interface for searching across a BIDS datasets based on various subject clinical-demographic and imaging parameters.

• nipopy:

  Lightweight neuroimaging workflow manager to help with DICOM to BIDS conversion and running BIDS apps.

• OpenNeuro:

  A free and open platform for validating and sharing BIDS-compliant data.

• PRFmodel:

  a set of tools to fit population receptive field models to BIDS datasets

• PyBIDS:

  Python package to quickly parse / search the components of a BIDS dataset. It also contains functionality for running analyses on your data.

• rbids:

  aims to make BIDS datasets more easily accessible for packages written in R

• spm_2_bids:

  a tool convert SPM preprocessed output to BIDS derivatives (trying to follow BEP12)

• psychopy-bids:

  A psychopy plugin to help easily output a BIDS dataset, including events.tsv and beh.tsv files when running experiments with psychopy.