Metadata-Version: 2.4
Name: QSIPrep
Version: 26.0.0
Summary: QSIPrep builds workflows for preprocessing and reconstructing q-space images
Project-URL: Homepage, https://github.com/pennlinc/qsiprep
Project-URL: Documentation, https://www.qsiprep.readthedocs.io
Project-URL: Paper, https://doi.org/10.1038/s41592-022-01458-7
Project-URL: Docker Images, https://hub.docker.com/r/pennlinc/qsiprep/tags/
Author: The PennLINC developers
License: Copyright (c) 2015-2018, the BBL developers team.
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        * Redistributions of source code must retain the above copyright notice, this
          list of conditions and the following disclaimer.
        
        * Redistributions in binary form must reproduce the above copyright notice,
          this list of conditions and the following disclaimer in the documentation
          and/or other materials provided with the distribution.
        
        * Neither the name of qsiprep nor the names of its
          contributors may be used to endorse or promote products derived from
          this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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License-File: LICENSE
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Image Recognition
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Description-Content-Type: text/x-rst

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.

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