Processing workflow from BIDS MRI to ready to use modality based connectomes and surface .
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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.
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.
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).
Should you have any problems, questions, or suggestions about micapipe,
please post an issue or
formulate a pull request
on our repository.
Micapipe is developed by MICA-lab and
collaborators at the McConnell Brain Imaging Center of the Montreal
Neurological Institute.

Content type
Image
Digest
sha256:f9dc9bd0c…
Size
21 GB
Last updated
over 2 years ago
docker pull micalab/micapipe:v0.2.3