Micapipe

Multimodal connectome processing with the micapipe

micapipe is developed by MICA-lab at McGill University for use at the Neuro, McConnell Brain Imaging Center (BIC).

The main goal of this pipeline is to provide a semi-flexible and robust framework to process MRI images and generate ready to use modality based connectomes.
The micapipe utilizes a set of known software dependencies, different brain atlases, and software developed in our laboratory. The basic cutting edge processing of our pipelines aims the T1 weighted images, resting state fMRI, quantitative MRI and Diffusion weighted images.

<img src="img/micapipe_logo_black.jpg" alt="micapipe" width="30%">

Documentation

You can find the documentation in micapipe.readthedocs.io

Container

You can find the latest version of the container in Docker

Reference

Raúl R. Cruces, Jessica Royer, Peer Herholz, Sara Larivière, Reinder Vos de Wael, Casey Paquola, Oualid Benkarim, Bo-yong Park, Janie Degré-Pelletier, Mark Nelson, Jordan DeKraker, Ilana Leppert, Christine Tardif, Jean-Baptiste Poline, Luis Concha, Boris C. Bernhardt. (2022). Micapipe: a pipeline for multimodal neuroimaging and connectome analysis. NeuroImage, 2022, 119612, ISSN 1053-8119. doi: https://doi.org/10.1016/j.neuroimage.2022.119612

Workflow

Advantages

• Microstructure Profile Covariance (Paquola C et al. Plos Biology 2019).
• Multiple parcellations (18 x 3).
• Includes cerebellum and subcortical areas.
• Surface based analysis.
• Latest version of software dependencies.
• Ready to use outputs.
• Easy to use.
• Standardized format (BIDS).

Dependencies

| Software | Version | Further info | |------------|---------------|--------------|
| dcm2niix | v1.0.20190902 | https://github.com/rordenlab/dcm2niix | | Freesurfer | 7.3.2 | https://surfer.nmr.mgh.harvard.edu/ | | FSl | 6.0.2 | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki | | AFNI | 20.3.03 | https://afni.nimh.nih.gov/download | | MRtrix3 | 3.0.1 | https://www.mrtrix.org | | ANTs | 2.3.3 | https://github.com/ANTsX/ANTs | | workbench | 1.3.2 | https://www.humanconnectome.org/software/connectome-workbench | | FIX | 1.06 | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIX | | R | 3.6.3 | https://www.r-project.org | | python | 3.9.16 | https://www.python.org/downloads/ | | conda | 22.11.1 | https://docs.conda.io/en/latest/ |

The FIX package (FMRIB's ICA-based Xnoiseifier) requires FSL, R and one of MATLAB Runtime Component, full MATLAB or Octave. We recommend the use of the MATLAB Runtime Component. Additionally, it requires the following R libraries: 'kernlab 0.9.24','ROCR 1.0.7','class 7.3.14','party 1.0.25','e1071 1.6.7','randomForest 4.6.12'

python mandatory packages conda

| Package | Version | |------------------------|------------| | nibabel | 4.0.2 | | numpy | 1.21.5 | | pandas | 1.4.4 | | vtk | 9.2.2 | | pyvirtualdisplay | 3.0 |

python mandatory packages pip

| Package | Version | |------------------------|------------| | argparse | 1.1 | | brainspace | 0.1.10 | | tedana | 0.0.12 | | pyhanko | 0.17.2 | | mapca | 0.0.3 | | xhtml2pdf | 0.2.9 | | oscrypto | 1.3.0 | | tzdata | 2022.7 | | arabic-reshaper | 3.0.0 | | cssselect2 | 0.7.0 | | pygeodesic | 0.1.8 | | seaborn | 0.11.2 |

R libraries

| library | version | |:------------:|:--------:| | scales | 1.1.1 | | randomForest | 4.6-14 | | e1071 | 1.7-4 | | party | 1.3-5 | | strucchange | 1.5-2 | | sandwich | 2.5-1 | | zoo | 1.8-7 | | modeltools | 0.2-23 | | mvtnorm | 1.1-1 | | class | 7.3-17 | | ROCR | 1.0-11 | | kernlab | 0.9-29 | | coin | 1.3-1 | | pkgconfig | 2.0.3 | | MASS | 7.3-51.5 | | libcoin | libcoin | | Matrix | 1.2-18 |