Browsing by Author "Zhuo, Jiachen"

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    Application of phase-based motion outlier detection to infant dMRI
    (ISMRM, 2020) Elsaid, Nahla M. H.; Zhuo, Jiachen; Prince, Jerry L.; Wu, Yu-Chien; Radhakrishnan, Rupa; Radiology and Imaging Sciences, School of Medicine
    Detecting and eliminating motion-corrupted slices is crucial in diffusion MRI (dMRI), and particularly essential in imaging neonates. Conventional magnitude-based outlier rejection methods are intensity-based and can usually detect and correct intra-volume movement but can miss outliers in cases of small continuous motions. Phase-based methods can be used to detect motion independently, regardless of the slice-to-volume location. The phase-based method is reasonably accurate and computationally fast, and may be better suited for real-time detection of motion in dMRI. Combining magnitude and phase methods could produce the best results. Here, we evaluate the phase-based method versus the magnitude-based method in neonatal data.
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    Phase Image Texture Analysis for Motion Detection in Diffusion MRI (PITA-MDD)
    (Elsevier, 2019-10) Elsaid, Nahla M. H.; Prince, Jerry L.; Roys, Steven; Gullapalli, Rao P.; Zhuo, Jiachen; Radiology and Imaging Sciences, School of Medicine
    Purpose 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. Methods 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. Results 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. Conclusion 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.