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Diffusion Imaging in the Rat Cervical Spinal Cord
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Quality Control of Diffusion Weighted Images.

Zhexing Liu1, Yi Wang1, Guido Gerig2

  • 1Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA 27510.

Proceedings of Spie--The International Society for Optical Engineering
|December 20, 2013
PubMed
Summary
This summary is machine-generated.

Automating Diffusion Tensor Imaging (DTI) quality control (QC) using DTIPrep enhances brain white matter analysis. This open-source tool ensures robust DTI data by addressing artifacts and improving consistency in Diffusion Weighted Imaging (DWI) studies.

Keywords:
Diffusion Tensor ImagingDiffusion Weighted ImagingEddy Current ArtifactIntensity ArtifactMotion ArtifactQuality Control

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Area of Science:

  • Neuroimaging
  • Medical Physics
  • Biomedical Engineering

Background:

  • Diffusion Tensor Imaging (DTI) is crucial for assessing brain white matter integrity.
  • Diffusion Weighted Imaging (DWI) data used for DTI is prone to low signal-to-noise ratio (SNR) and artifacts.
  • Current manual DTI quality control (QC) is inconsistent, time-consuming, and subjective.

Purpose of the Study:

  • To develop an automated framework for DWI data quality control.
  • To introduce DTIPrep, an open-source tool for streamlining DTI QC.
  • To improve the reliability and efficiency of DTI analysis in neuroimaging studies.

Main Methods:

  • Development of an automated DWI QC pipeline.
  • Implementation of DTIPrep with protocoling and reporting features.
  • Validation of the DTIPrep framework on multiple DTI studies.

Main Results:

  • DTIPrep successfully automated the QC process for DWI datasets.
  • The tool demonstrated effectiveness in handling artifacts and improving data consistency.
  • Successful application in multi-site studies involving hundreds of DWI datasets.

Conclusions:

  • Automated DWI QC using DTIPrep provides a robust solution for DTI analysis.
  • DTIPrep enhances consistency and reduces subjectivity in DTI quality assessment.
  • The open-source nature of DTIPrep facilitates wider adoption in neuroimaging research.