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Diffusion-Relaxation Suite
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**A Toolkit for Multicomponent Modeling of High-Dimensional Multiparametric MRI Data**

.. figure:: _static/images/DRCSI_inj_mouse_spectroscopic_Im_contour_1.png
    :name: fig_mosaic
    :align: right
    :figwidth: 40%

MRI generates images with millimeter-scale spatial resolution, while many important biological features
occur at much smaller (microscopic) scales. Over the past several decades, MRI practitioners have used the
information derived from biophysical parameters (like relaxation and diffusion) to indirectly probe
microscopic tissue compartments using millimeter-scale data. While these approaches have been somewhat
successful, an innovative new paradigm has emerged in recent years that leverages multiparametric MRI data
(e.g., using relaxation and diffusion jointly in a higher-dimensional experiment) to probe tissue microstructure
with an unprecedented level of detail. 

:bdg-primary-line:`Diffusion-Relaxation Suite` is an open-source software package that provides novel analysis methods to identify
and separate multiple microstructural tissue compartments from MRI data using advanced constrained estimation
techniques. These form the central component of an end-to-end image preprocessing pipeline that includes
steps for registration and visualization. 
This package is especially designed for multiparametric acquisitions and provides novel tools to evaluate
estimation quality and to optimize multiparametric acquisition protocols. 

We have implemented these approaches into an easy-to-use software package, 
which provides the broader imaging community with easy access to these powerful approaches.

.. * Say something about diffusion-relaxation imaging and why it is useful/important.
.. * Say something about what this software does.
.. * Say something more about why it is important for diffusion-relaxation imaging or other multiparametric data.


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Features
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.. dropdown:: Image Registration

    Describe functionality


.. dropdown:: Phantom Generation

    Describe functionality


.. dropdown:: Spectral Estimation

    Describe functionality


.. dropdown:: Spectral Visualization

    Describe functionality


.. dropdown:: GPU-enabled Containerized Installation (Docker, Singularity)

    Describe benefits

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Team
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:bdg-link-primary:`Justin Haldar <https://mr.usc.edu>` (PI), :bdg-link-primary:`Debdut Mandal <https://www.linkedin.com/in/deeman/>`, :bdg-link-primary:`Anand Joshi <https://sipi.usc.edu/~ajoshi/>`, and :bdg-link-primary:`David Shattuck <http://shattuck.bmap.ucla.edu>`.

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Acknowledgements
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This project is supported in part by :bdg-link-primary:`NIH Grant R56-EB034349 <https://reporter.nih.gov/project-details/10861533>`.

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Licenses
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GPLv2-only for most code.