Back to Search
Start Over
Phase Image Texture Analysis for Motion Detection in Diffusion MRI (PITA-MDD).
- Source :
-
Magnetic Resonance Imaging (0730725X) . Oct2019, Vol. 62, p228-241. 14p. - Publication Year :
- 2019
-
Abstract
- Pronounced spin phase artifacts appear in diffusion-weighted imaging (DWI) with only minor subject motion. While DWI data corruption is often identified as signal drop out in diffusion-weighted (DW) magnitude images, DW phase images may have higher sensitivity for detecting subtle subject motion. This article describes a novel method to return a metric of subject motion, computed using an image texture analysis of the DW phase image. This Phase Image Texture Analysis for Motion Detection in dMRI (PITA-MDD) method is computationally fast and reliably detects subject motion from diffusion-weighted images. A threshold of the motion metric was identified to remove motion-corrupted slices, and the effect of removing corrupted slices was assessed on the reconstructed FA maps and fiber tracts. Using a motion-metric threshold to remove the motion-corrupted slices results in superior fiber tracts and fractional anisotropy maps. When further compared to a state-of-the-art magnitude-based motion correction method, PITA-MDD was able to detect comparable corrupted slices in a more computationally efficient manner. In this study, we evaluated the use of DW phase images to detect motion corruption. The proposed method can be a robust and fast alternative for automatic motion detection in the brain with multiple applications to inform prospective motion correction or as real-time feedback for data quality control during scanning, as well as after data is already acquired. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DIFFUSION magnetic resonance imaging
*IMAGE analysis
*MOTION analysis
Subjects
Details
- Language :
- English
- ISSN :
- 0730725X
- Volume :
- 62
- Database :
- Academic Search Index
- Journal :
- Magnetic Resonance Imaging (0730725X)
- Publication Type :
- Academic Journal
- Accession number :
- 137947280
- Full Text :
- https://doi.org/10.1016/j.mri.2019.07.009