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micalab/micapipe

By micalab

Updated over 2 years ago

Processing workflow from BIDS MRI to ready to use modality based connectomes and surface .

Image
Data science
Databases & storage
5

9.3K

micalab/micapipe repository overview

Welcome to micapipe's docker!

micapipe

Micapipe is a processing pipeline providing a robust framework to analyze multimodal MRI data. This pipeline integrates processing streamlines for T1-weighted, microstructure-sensitive, diffusion-weighted, and resting-state functional imaging to facilitate the development of multiscale models of neural organization. For this purpose, we leverage several specialized software packages to bring BIDS-formatted raw MRI data to fully-processed surface-based feature matrices.

Reproducibility

To encourage reproducibility and robustness of investigations using micapipe, we provide a fully containerized version of the pipeline in the form of a Docker container. Step-by-step tutorials are provided for bare metal and containerized installations. We encourage users to use containerized versions, offered through Docker and Singularity, given the large number of software dependencies used by the pipeline to handle multiple MRI data modalities.

Datasets

Micapipe has been tested on several locally acquired datasets, as well as openly available repositories such as Cambridge Centre for Ageing and Neuroscience (Cam-CAN), PREVENT-AD, Healthy Brain Network, and Microstructure-Informed Connectomis (MICs).

Development and getting involved

Should you have any problems, questions, or suggestions about micapipe, please post an issue or formulate a pull request on our repository.

Core development team

Micapipe is developed by MICA-lab and collaborators at the McConnell Brain Imaging Center of the Montreal Neurological Institute.

  • Raúl Rodríguez-Cruces, MICA Lab - Montreal Neurological Institute
  • Alex Ngo, MICA Lab - Montreal Neurological Institute
  • Jessica Royer, MICA Lab - Montreal Neurological Institute
  • Sara Larivière, MICA Lab - Montreal Neurological Institute
  • Peer Herholz, NeuroDataScience, ORIGAMI lab - Montreal Neurological Institute
  • Jordan DeKraker, MICA Lab - Montreal Neurological Institute
  • Youngeun Hwang, MICA Lab - Montreal Neurological Institute
  • Nicole Eichert, Jesus College, Oxford
  • Yezhou Wang, MICA Lab - Montreal Neurological Institute
  • Casey Paquola, MICA Lab - Montreal Neurological Institute
  • Oualid Benkarim, MICA Lab - Montreal Neurological Institute
  • Boris Bernhardt, MICA Lab - Montreal Neurological Institute

Workflow

workflow

Tag summary

Content type

Image

Digest

sha256:f9dc9bd0c

Size

21 GB

Last updated

over 2 years ago

docker pull micalab/micapipe:v0.2.3