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Updated: Aug 1, 2025

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury
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Dmriprep: open-source diffusion MRI quality control framework with graphical user interface.

Johanna Dubos1, Sang Kyoon Park1, Roza Vlasova1

  • 1Dept Psychiatry, University of North Carolina, Chapel Hill, NC, USA.

Proceedings of Spie--The International Society for Optical Engineering
|April 24, 2023
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Summary
This summary is machine-generated.

This study introduces dtiplayground, a new diffusion MRI analysis environment with an enhanced quality control module, dmriprep, to address artifacts and improve data analysis for neuroimaging studies.

Keywords:
diffusion MRIopen sourcepreprocessingquality control

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Area of Science:

  • Neuroimaging
  • Diffusion MRI Analysis

Background:

  • Diffusion MRI (dMRI) is vital for studying white matter microstructure and connectivity.
  • Low signal-to-noise ratio and artifacts in dMRI data necessitate robust quality control (QC).
  • Existing tools like DTIPrep require modernization due to advancements in acquisition and artifact correction.

Purpose of the Study:

  • To present dtiplayground, a novel diffusion MRI analysis environment.
  • To introduce dmriprep, a redesigned and enhanced QC module with a graphical user interface (dmriprep-ui).
  • To provide a unified, user-friendly tool for comprehensive dMRI data QC.

Main Methods:

  • Development of dtiplayground, integrating in-house code with FSL and dipy.
  • Redesign of the DTIPrep QC tool into the dmriprep module.
  • Implementation of dmriprep-ui for user-friendly interaction.
  • Addressing artifacts including eddy currents, motion, and susceptibility.

Main Results:

  • dtiplayground offers a comprehensive framework for dMRI QC.
  • dmriprep effectively addresses a wide range of common dMRI artifacts.
  • The graphical user interface facilitates thorough visual QC and automated tractography assessment.

Conclusions:

  • dtiplayground and dmriprep provide a modern, open-source solution for dMRI quality control.
  • The enhanced QC tools improve the reliability and accuracy of diffusion MRI analyses.
  • This framework supports the neuroimaging community with advanced dMRI data processing capabilities.