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Comprehensive reconstruction of multi-shot multi-channel diffusion data using mussels
Conference proceeding

Comprehensive reconstruction of multi-shot multi-channel diffusion data using mussels

Merry Mani, Vincent Magnotta, Douglas Kelley and Mathews Jacob
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Vol.2016-, pp.1107-1110
08/2016
DOI: 10.1109/EMBC.2016.7590897
PMID: 28268519
url
https://www.ncbi.nlm.nih.gov/pmc/articles/7902245View
Open Access

Abstract

Echo planar imaging (EPI)-based magnetic resonance imaging (MRI) data are often corrupted by Nyquist ghost artifacts resulting from odd-even shifts of the EPI read-outs. Algorithms that corrects for the Nyquist ghost artifacts rely on calibration scans that are collected prior to the data acquisition. However, a more complex pattern of ghosting artifacts arises when diffusion-weighted data are acquired using segmented k-space EPI read-outs. The additional under-sampling present in the segmented acquisitions and the inter-shot motion during diffusion weighted acquistion cause ghosting artifacts in addition to the EPI ghosting arising from odd-even shifts. We propose a comprehensive method that can remove the Nyquist-ghosting artifacts as well as the inter-shot motion-induced ghosting artifacts in diffusion weighted images in a single step from partial Fourier data without the need for a calibration scan. We show very high quality diffusion data recovery using the proposed method.
Magnetic resonance imaging Motion segmentation matrix completion MRI low-rank Nonhomogeneous media multi-shot diffusion Calibration Mathematical model Image reconstruction annihilating filter

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