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Getting started

  • Installation
    • Docker
    • Singularity
      • Preparing a Singularity image (Singularity version >= 2.5)
      • Preparing a Singularity image (Singularity version < 2.5)
      • Running a Singularity Image
    • “Bare-metal” installation
      • Set the environment
      • External Dependencies
  • Usages Notes
    • Data format
    • Micapipe usage overview
    • Module flags
      • T1w Structural Processing
      • Microstructure-sensitive Image Processing
      • Flair
      • DWI Processing
      • Functional MRI
      • Superficial White Matter SWM
      • Microstructural Superficial White Matter Covariance
      • Integrated Quality Control
    • More options
  • What’s new?
    • v0.2.+ ‘Northern Flicker’
    • v0.2.3, Jan 18, 2024
    • v0.2.2, Aug 9, 2023
    • v0.2.1, Jun 26, 2023
    • v0.2.0 ‘Northern Flicker’, Jun 16, 2023
    • v0.1.5, Jun 10, 2023
    • v0.1.4 ‘Roadrunner’, Nov 3, 2022
    • v0.1.2
    • v0.1.1
    • v0.1.0 ‘Wobbly’

Processing modules

  • Structural processing
    • -proc_structural
    • -proc_surf
    • -post_structural
    • -GD
  • Diffusion-weighted imaging processing
    • -proc_dwi
    • -SC
  • func processing
    • -proc_func
  • Microstructural profile covariance
    • -MPC
  • Fluid attenuated inversion recovery
    • -proc_flair
  • Superficial White Matter
    • -SWM
  • Microstructural Superficial White Matter Covariance (SWMcov)
    • -MPC_SWM
  • Quality control
    • Individual QC
    • Group level QC

Additional tools

  • From DICOMS to BIDS: mic2bids
    • MICs dataset
  • micapipe_cleanup
  • micapipe_anonymize
  • Automatic Bundle Segmentation

Tutorials

  • Processing step by step: start to finish with micapipe
    • 1. Download an open access dataset
    • 2. Converting to BIDS
    • 3. Validating BIDS
    • 4. Running micapipe
    • 5. Visualize the QC report
  • Processing databases with micapipe
    • Microstructure-Informed Connectomics (MICs)
    • Epilepsy and Cognition (EpiC-UNAM)
    • Cambridge Centre for Ageing and Neuroscience (Cam-CAN)
    • SUDMEX_CONN
    • Midnight Scan Club MSC
    • Auditory localization with 7T fMRI (Audiopath)
  • Main output matrices
    • Download code examples: matrices
    • Organization of the outputs
    • Structural connectome
      • Full structural connectome
      • Full structural connectome edge lengths
    • Functional connectome
      • Resting state time series
    • MPC connectome
      • Intensity profiles
    • Geodesic distance connectome
  • Surface visualization
    • Setting the environment
    • Load the surfaces
    • Morphology
      • Thickness: Inflated native surface
      • Thickness: fsaverage5
      • Thickness: fsLR-32k
      • Thickness: fsLR-5k
      • Curvature: Native inflated surface
      • Curvature: fsaverage5
      • Curvature: fsLR-32k
      • Curvature: fsLR-5k
    • fsLR-32k
      • fsLR-32k: Pial surface
      • fsLR-32k: Middle surface
      • fsLR-32k: White matter surface
    • Native sphere
    • Superficial White Matter (SWM) in fsnative surface
      • SWM Surfaces
      • SWM 1mm
      • SWM 2mm
      • SWM 3mm
    • /maps: fsnative, fsaverage5, fsLR-32k and fsLR-5k
      • T1map on fsnative
      • T1map on fsaverage5 native
      • T1map on fsLR-32k native
      • T1map on fsLR-5k native
    • /maps: fsaverage5, fsLR-32k and fsLR-5k on standard
      • T1map on fsaverage5 standard
      • T1map on fsLR-32k stardard
      • T1map on fsLR-5k stardard
    • Atlas labels on surface
      • Schaefer-400 labels
      • Extra: Economo labels
    • Download code examples: Surfaces
  • Building gradients
    • python environment
      • Loading the surfaces
      • Global variables
    • Gradients from atlas based connectomes: single subject
      • Geodesic distance
      • Structural gradients
      • Functional gradients
      • MPC gradients
    • Load all matrices from a dataset processed
      • MPC gradients: ALL subjects mean
    • Download the code!: atlas based gradients
  • fsLR-5k gradients
    • Environment
    • Geodesic distance: single subject fsLR-5k
    • Structual connectome: single subject fsLR-5k
    • Functional connectome: single subject fsLR-5k
    • MPC T1map: single subject fsLR-5k
    • MPC T1map: ALL subjects fsLR-5k
    • Download the code!: fsLR-5k gradients
  • Fetch parcellations and matrix indexing
    • Matrix Indexing and Coverage
      • GD and MPC
      • SC: Structural Connectomes
      • FC: Functional Connectomes
    • Subcortical and Cerebellar Lookup Table
    • Cortical labels
      • Anatomy based parcellations
      • Histology based parcellation
      • Multimodal based parcellation
      • Functional based parcellation
      • Pseudo-random parcellation based on Desikan Killiany
    • Parcellated Connectomes
      • GD Connectomes fsLR-32k
      • GD Connectomes fsaverage5
      • Structural Connectomes fsLR-32k
      • Structural Connectomes fsaverage5
      • MPC Connectomes fsLR-32k
      • MPC Connectomes fsaverage5
      • FC Connectomes fsLR-32k
      • FC Connectomes fsaverage5
  • How to downsample a tractogram
    • Changes before and after downsampling a tractogram
      • Number of points
      • Streamlines lengths
    • Code example in python
  • FAQ
    • Registration issues
    • Surface issues
    • Resting state issues
    • DWI issues
    • Parcellation issues

References & Acknowledgements

  • Citing micapipe
  • References
    • Software
    • R Packages
    • python packages
    • Datasets
    • Parcellations
    • Other sources
    • Functions
  • Acknowledgements
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