Metadata-Version: 2.1
Name: qsiprep
Version: 0.15.3
Summary: qsiprep builds workflows for preprocessing and reconstructing q-space images
Home-page: https://github.com/pennbbl/qsiprep
Author: The PennBBL developers
Author-email: Matthew.Cieslak@pennmedicine.upenn.edu
Maintainer: Matt Cieslak
Maintainer-email: Matthew.Cieslak@pennmedicine.upenn.edu
License: 3-clause BSD
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.5
Description-Content-Type: text/x-rst; charset=UTF-8
Provides-Extra: datalad
Provides-Extra: doc
Provides-Extra: docs
Provides-Extra: duecredit
Provides-Extra: resmon
Provides-Extra: sentry
Provides-Extra: tests
Provides-Extra: all
License-File: LICENSE

qsiprep borrows heavily from FMRIPREP to build workflows for preprocessing q-space images
such as Diffusion Spectrum Images (DSI), multi-shell HARDI and compressed sensing DSI (CS-DSI).
It utilizes Dipy and ANTs to implement a novel high-b-value head motion correction approach
using q-space methods such as 3dSHORE to iteratively generate head motion target images for each
gradient direction and strength.

Since qsiprep uses the FMRIPREP workflow-building strategy, it can also generate methods
boilerplate and quality-check figures.

Users can also reconstruct orientation distribution functions (ODFs), fiber orientation
distributions (FODs) and perform tractography, estimate anisotropy scalars and connectivity
estimation using a combination of Dipy, MRTrix and DSI Studio using a JSON-based pipeline
specification.

[Documentation `qsiprep.org <https://qsiprep.readthedocs.io>`_]


