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Preprocessing and reconstruction of diffusion MRI
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README.rst

QSIprep: Preprocessing and analysis of q-space images

Documentation Status https://circleci.com/gh/PennBBL/qsiprep/tree/master.svg?style=svg

Full documentation at https://qsiprep.readthedocs.io

About

qsiprep configures pipelines for processing diffusion-weighted MRI (dMRI) data. The main features of this software are

  1. A BIDS-app approach to preprocessing nearly all kinds of modern diffusion MRI data.
  2. Automatically generated preprocessing pipelines that correctly group, distortion correct, motion correct, denoise, coregister and resample your scans, producing visual reports and QC metrics.
  3. A system for running state-of-the-art reconstruction pipelines that include algorithms from Dipy_, MRTrix_, `DSI Studio`_ and others.
  4. A novel motion correction algorithm that works on DSI and random q-space sampling schemes

Preprocessing

The preprocessing pipelines are built based on the available BIDS inputs, ensuring that fieldmaps are handled correctly. The preprocessing workflow performs head motion correction, susceptibility distortion correction, MP-PCA denoising, coregistration to T1w images, spatial normalization using ANTs_ and tissue segmentation.

Reconstruction

The outputs from the :ref:`preprocessing_def` pipelines can be reconstructed in many other software packages. We provide a curated set of :ref:`recon_workflows` in qsiprep that can run ODF/FOD reconstruction, tractography, Fixel estimation and regional connectivity.

Note

The qsiprep pipeline uses much of the code from FMRIPREP. It is critical to note that the similarities in the code do not imply that the authors of FMRIPREP in any way endorse or support this code or its pipelines.

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