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January 23, 2024 · View on GitHub

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Multimodal connectome processing with the micapipe

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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.

micapipe

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

micapipe

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

SoftwareVersionFurther info
dcm2niixv1.0.20190902https://github.com/rordenlab/dcm2niix
Freesurfer7.3.2https://surfer.nmr.mgh.harvard.edu/
FSl6.0.2https://fsl.fmrib.ox.ac.uk/fsl/fslwiki
AFNI20.3.03https://afni.nimh.nih.gov/download
MRtrix33.0.1https://www.mrtrix.org
ANTs2.3.3https://github.com/ANTsX/ANTs
workbench1.3.2https://www.humanconnectome.org/software/connectome-workbench
FIX1.06https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIX
R3.6.3https://www.r-project.org
python3.9.16https://www.python.org/downloads/
conda22.11.1https://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

PackageVersion
nibabel4.0.2
numpy1.21.5
pandas1.4.4
vtk9.2.2
pyvirtualdisplay3.0

python mandatory packages pip

PackageVersion
argparse1.1
brainspace0.1.10
tedana0.0.12
pyhanko0.17.2
mapca0.0.3
xhtml2pdf0.2.9
oscrypto1.3.0
tzdata2022.7
arabic-reshaper3.0.0
cssselect20.7.0
pygeodesic0.1.8
seaborn0.11.2

R libraries

libraryversion
scales1.1.1
randomForest4.6-14
e10711.7-4
party1.3-5
strucchange1.5-2
sandwich2.5-1
zoo1.8-7
modeltools0.2-23
mvtnorm1.1-1
class7.3-17
ROCR1.0-11
kernlab0.9-29
coin1.3-1
pkgconfig2.0.3
MASS7.3-51.5
libcoinlibcoin
Matrix1.2-18