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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.
Abstract:
In the last decade, investigating white matter microstructure and connectivity via diffusion MRI (dmri) has become a crucial cornerstone in neuroimaging studies. However, even modern dmri sequences have inherently a low signal-to-noise ratio and long acquisition times, depending on the spatial resolution. Furthermore, many types of artifacts complicate the appropriate analysis of dmri, necessitating appropriate quality control (QC) procedures, including exclusion and/or correction of inappropriate/erroneous dmri data. Our group has been developing and promoting QC procedures and tools to the community to enable appropriate dmri analyses. Since its development in 2011, our DTIPrep QC tool has become a major tool due its ease of use and dmri QC performance. Over the years, novel developments in acquisition and artifact correction methods have led to a need to modernize DTIPrep. Here, we present a novel diffusion MRI analysis environment called dtiplayground with a fully redesigned and significantly enhanced QC module dmriprep, and its graphical user interface dmriprep-ui, building on in-house developed code, FSL and dipy. The user interface is designed to be a unified, user friendly tool for thorough QC of dMRI data.Artifacts addressed by dmriprep include eddy-currents, head motion, bed vibration and pulsation, venetian blind artifacts, slice-wise and gradient-wise intensity inconsistencies, and susceptibility artifacts. It further provides an user interface for visual QC of gradients and automated tractography. In summary, our work presents a novel open-source framework for modern comprehensive dmri QC.
Insights
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.
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.
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