In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, gender identity and expression, level of experience,
+nationality, personal appearance, race, religion, or sexual identity and
+orientation.
Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at bids.maintenance@gmail.com. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
A lot of times, making a PR adhere to the standards above can be difficult.
+If the maintainers notice anything that we'd like changed, we'll ask you to
+edit your PR before we merge it. There's no need to open a new PR, just edit
+the existing one. If you're not sure how to do that,
+here is a guide
+on the different ways you can update your PR so that we can merge it.
The Neurostars discourse forum
+ run by the International Neuroinformatics Coordinating Facility (INCF)
+ with its own BIDS category.
+ With a lot BIDS users and developers,
+ it is the best place where to ask BIDS related questions.
+
+
+
BIDS mailing list:
+ a google group for announcements and discussions around BIDS.
Autobids: Automated Dicom to BIDS and pipelines using compute canada. From the Center for Functional and Metabolic Mapping (CFMM) at Western’s Robarts Research Institute.
+
+
BIDScoin: BIDScoin converts your source-level neuroimaging data to BIDS
+
+
BIDSconvertR: 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
+
+
bidsify: Tool to convert source MRI datasets to BIDS-compatible datasets.
+
+
bidskit: Utility functions for working with DICOM and BIDS neuroimaging data.
+
dac2bids: Create a BIDS structure for a DICOM folder.
+
+
Data2Bids: Converts MRI files from extension supported by nibabel into NIfTI and convert them to BIDS
+
+
Dcm2Bids: converts DICOM files using dcm2niix into BIDS
+
+
Explore ASL: Convert DICOM and NIFTI data to the ASL-BIDS format.
+
+
ezBIDS: 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.
+
+
HeuDiConv: A flexible DICOM converter for organizing brain imaging data into structured directory layouts
+
mercure-dcm2bids: 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.
+
+
niix2bids: Use this package as a command line to organize your Nifti dataset into BIDS.
+
PET2BIDS: Helps you convert your PET data! raw PET scanner files (for example ecat, dicom) and additional side file like excel sheets.
+
+
ReproIn: HeuDiConv-based turnkey solution: a setup for automatic generation of shareable, version-controlled BIDS datasets from MR scanners.
+
+
SAMRI: 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.
+
+
XNAT2BIDS: Simple xnat pipeline to convert DICOM scans to BIDS-compatible output (nii+json).
+
EEG2BIDS: A tool for converting raw EEG and iEEG data into the BIDS standard data structure, prepared for LORIS (Longitudinal Online Research and Imaging System).
+
CPAC: BIDS Application for the Configurable Pipeline for the Analysis of Connectomes (C-PAC)
+
+
DPARSF: Docker version of DPARSF, also deployed at OpenNeuro.org
+
+
freesurfer: BIDS app wrapping recon-all from FreeSurfer
+
+
HCPPipelines: A BIDS App for minimal preprocessing using the HCP Pipelines
+
+
hyperalignment: Hyperalignment is a functional alignment method that aligns subjects' brain data in a high-dimensional space of voxels/features.
+
+
mindboggle: Improve the accuracy, precision, and consistency of automated labeling and shape analysis of human brain image data
+
+
MRtrix3_connectome: Generate subject connectomes from raw BIDS data & perform inter-subject connection density normalisation, using the MRtrix3 software package.
+
+
ndmg: BIDS app for NeuroData's MRI to Graphs pipeline
+
+
nipypelines: Preprocess functional tasks in a BIDS dataset.
+
+
oppni: runs fast optimization of preprocessing pipelines for BOLD fMRI
+
+
PyMVPA: runs MVPA and RSA analysis BIDS bold derivative data
+
rs_signal_extract: BIDS App for resting state signal extraction using nilearn.
+
+
rsHRF: Resting state HRF estimation from BOLD-fMRI signal
+
+
SPM: BIDS App containing an instance of the SPM software.
+
+
tracula: implements Freesurfer's TRACULA (TRActs Constrained by UnderLying Anatomy) tool for cross-sectional as well as longitudinal (multi session) input data.
+
+
connectomemapper3: Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.
+
+
bidsMReye: BIDS app using deepMReye to decode eye motion for fMRI time series data.
+
funcmasker-flex: BIDS App for U-net brain masking of fetal bold MRI
+
+
hippunfold: BIDS App for Hippunfold (automated hippocampal unfolding and subfield segmentation)
+
+
mialsuperresolutiontoolkit: The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ and Python processing and workflow tools necessary to perform motion-robust super-resolution fetal MRI reconstruction in the BIDS Apps framework.
+
+
micapipe: micapipe from the Multimodal imaging and connectome analysis lab (http://mica-mni.github.io) at the Montreal Neurological Institute. Read The Docs documentation below
+
+
dmriprep: dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
+
+
fmriprep: fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
+
+
mriqc: Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain
+
+
nibabies: Processing tools for magnetic resonance images of infant brains
+
multiscalebrainparcellator: Multi-Scale Brain Parcellator, part of the Connectome Mapping Toolkit (CMTK), is a BIDS App that implements a full anatomical MRI processing pipeline, from raw T1w data to structural brain parcellation at five different scales.
+
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.
+
bids-cfood: a module to handle BIDS dataset for the caosDB data crawler
+
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.
+
+
bids2cite: package to interactively update dataset_description.json and generate citation files (for example datacite.yml) for BIDS datasets.
+
+
bidser: Working with Brain Imaging Data Structure in R
+
+
BIDSHandler: Python module allowing complete manipulation of BIDS data
+
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)
+
Ongoing community proposals for extending the BIDS specification to new datatypes (raw),
+to specify how to organized processed data (derivatives),
+or interoperating with BIDS datasets.
+
Make sure to check the list to see if some people are not already working
+on making sure BIDS supports your favorite datatype.
The Neurostars discourse forum run by the International Neuroinformatics Coordinating Facility (INCF) with its own BIDS category. With a lot BIDS users and developers, it is the best place where to ask BIDS related questions.
BIDS mailing list: a google group for announcements and discussions around BIDS.
BIDS in the Brainhack mattersmost: mattermost is the open source equivalent of slack and the Brainhack instance has over 5000 members with its own channel dedicated BIDS channel.
Autobids: Automated Dicom to BIDS and pipelines using compute canada. From the Center for Functional and Metabolic Mapping (CFMM) at Western\u2019s Robarts Research Institute.
BIDScoin: BIDScoin converts your source-level neuroimaging data to BIDS
BIDSconvertR: 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
bidsify: Tool to convert source MRI datasets to BIDS-compatible datasets.
bidskit: Utility functions for working with DICOM and BIDS neuroimaging data.
BIDSme:
BMAT:
BrkRaw: For a preclinical Bruker MRI scanner
Clinica:
dac2bids: Create a BIDS structure for a DICOM folder.
Data2Bids: Converts MRI files from extension supported by nibabel into NIfTI and convert them to BIDS
Dcm2Bids: converts DICOM files using dcm2niix into BIDS
Explore ASL: Convert DICOM and NIFTI data to the ASL-BIDS format.
ezBIDS: 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.
HeuDiConv: A flexible DICOM converter for organizing brain imaging data into structured directory layouts
Horos (Osirix) export plugin: Horos plugin for BIDS output.
mercure-dcm2bids: 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.
niix2bids: Use this package as a command line to organize your Nifti dataset into BIDS.
OpenfMRI2BIDS: Convert OpenfMRI dataset to BIDS
PET2BIDS: Helps you convert your PET data! raw PET scanner files (for example ecat, dicom) and additional side file like excel sheets.
ReproIn: HeuDiConv-based turnkey solution: a setup for automatic generation of shareable, version-controlled BIDS datasets from MR scanners.
SAMRI: 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.
XNAT2BIDS: Simple xnat pipeline to convert DICOM scans to BIDS-compatible output (nii+json).
EEG2BIDS: A tool for converting raw EEG and iEEG data into the BIDS standard data structure, prepared for LORIS (Longitudinal Online Research and Imaging System).
EEGLAB: See plugins
FieldTrip - data2bids:
MNE-BIDS: MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.
sovabids: A Python package for the automatic conversion of EEG datasets to the BIDS standard, with a focus on making the most out of metadata.
antsCorticalThickness: BIDS App for calculating cortical thickness using ANTs
baracus: Predicts brain age, based on data from Freesurfer 5.3
brainiak-srm: This is the BIDS-app version of the Shared Response Model (SRM) of BrainIAK
BrainSuite: BrainSuite's structural, diffusion, and functional MRI processing pipelines with QC functionalities.
BROCCOLI: BIDS App for BROCCOLI
CPAC: BIDS Application for the Configurable Pipeline for the Analysis of Connectomes (C-PAC)
DPARSF: Docker version of DPARSF, also deployed at OpenNeuro.org
freesurfer: BIDS app wrapping recon-all from FreeSurfer
HCPPipelines: A BIDS App for minimal preprocessing using the HCP Pipelines
hyperalignment: Hyperalignment is a functional alignment method that aligns subjects' brain data in a high-dimensional space of voxels/features.
mindboggle: Improve the accuracy, precision, and consistency of automated labeling and shape analysis of human brain image data
MRtrix3_connectome: Generate subject connectomes from raw BIDS data & perform inter-subject connection density normalisation, using the MRtrix3 software package.
ndmg: BIDS app for NeuroData's MRI to Graphs pipeline
nipypelines: Preprocess functional tasks in a BIDS dataset.
oppni: runs fast optimization of preprocessing pipelines for BOLD fMRI
PyMVPA: runs MVPA and RSA analysis BIDS bold derivative data
QAP: PCP Quality Assessment Protocol
rs_signal_extract: BIDS App for resting state signal extraction using nilearn.
rsHRF: Resting state HRF estimation from BOLD-fMRI signal
SPM: BIDS App containing an instance of the SPM software.
tracula: implements Freesurfer's TRACULA (TRActs Constrained by UnderLying Anatomy) tool for cross-sectional as well as longitudinal (multi session) input data.
connectomemapper3: Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.
bidsMReye: BIDS app using deepMReye to decode eye motion for fMRI time series data.
bidspm: an SPM centric BIDS app
fmriprep-fake: None
funcmasker-flex: BIDS App for U-net brain masking of fetal bold MRI
hippunfold: BIDS App for Hippunfold (automated hippocampal unfolding and subfield segmentation)
mialsuperresolutiontoolkit: The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ and Python processing and workflow tools necessary to perform motion-robust super-resolution fetal MRI reconstruction in the BIDS Apps framework.
micapipe: micapipe from the Multimodal imaging and connectome analysis lab (http://mica-mni.github.io) at the Montreal Neurological Institute. Read The Docs documentation below
dmriprep: dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
fmriprep: fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
mriqc: Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain
nibabies: Processing tools for magnetic resonance images of infant brains
BIDSonym: a BIDS app for pseudo-anonymization of neuroimaging data
aslprep: Preprocessing of arterial spin labeling data
qsiprep: Preprocessing and reconstruction of diffusion MRI
xcp_d: Post-processing of fMRIPrep, nibabies, HCP, and DCAN BOLD derivatives for functional connectivity analysis
fitlins: Fit Linear Models to BIDS Datasets
multiscalebrainparcellator: Multi-Scale Brain Parcellator, part of the Connectome Mapping Toolkit (CMTK), is a BIDS App that implements a full anatomical MRI processing pipeline, from raw T1w data to structural brain parcellation at five different scales.
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.
bids stats model: Validate BIDS statistical model. To learn more the BIDS stats model website
bids-cfood: a module to handle BIDS dataset for the caosDB data crawler
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.
bids2cite: package to interactively update dataset_description.json and generate citation files (for example datacite.yml) for BIDS datasets.
bidser: Working with Brain Imaging Data Structure in R
BIDSHandler: Python module allowing complete manipulation of BIDS data
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
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.
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)
Ongoing community proposals for extending the BIDS specification to new datatypes (raw), to specify how to organized processed data (derivatives), or interoperating with BIDS datasets.
Make sure to check the list to see if some people are not already working on making sure BIDS supports your favorite datatype.
If you are working on an extension proposal make sure to check our documentation regarding the BIDS extension proposal process.
Contributions welcome! Read the contribution guidelines first.
"},{"location":"code-of-conduct.html","title":"Contributor Covenant Code of Conduct","text":""},{"location":"code-of-conduct.html#our-pledge","title":"Our Pledge","text":"
In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.
This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.
Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at bids.maintenance@gmail.com. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Ensure your pull request adheres to the following guidelines:
Make sure you take care of this
And this as well
And don't forget to check this
Thank you for your suggestions!
"},{"location":"contributing.html#updating-your-pr","title":"Updating your PR","text":"
A lot of times, making a PR adhere to the standards above can be difficult. If the maintainers notice anything that we'd like changed, we'll ask you to edit your PR before we merge it. There's no need to open a new PR, just edit the existing one. If you're not sure how to do that, here is a guide on the different ways you can update your PR so that we can merge it.
"}]}
\ No newline at end of file
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new file mode 100644
index 0000000..31a59b3
--- /dev/null
+++ b/sitemap.xml
@@ -0,0 +1,18 @@
+
+
+
+ None
+ 2024-04-16
+ daily
+
+
+ None
+ 2024-04-16
+ daily
+
+
+ None
+ 2024-04-16
+ daily
+
+
\ No newline at end of file
diff --git a/sitemap.xml.gz b/sitemap.xml.gz
new file mode 100644
index 0000000..9d6cd45
Binary files /dev/null and b/sitemap.xml.gz differ
+
BIDScoin: BIDScoin converts your source-level neuroimaging data to BIDS
+ 
BIDSconvertR: 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
+ 
Explore ASL: Convert DICOM and NIFTI data to the ASL-BIDS format.
+ 
bids-matlab: MATLAB/Octave tools to interact with datasets conforming to the BIDS format
+ 
