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Free-Breathing and Ungated Dynamic MRI Using Navigator-Less Spiral SToRM
Journal article   Open access   Peer reviewed

Free-Breathing and Ungated Dynamic MRI Using Navigator-Less Spiral SToRM

Abdul Haseeb Ahmed, Ruixi Zhou, Yang Yang, Prashant Nagpal, Michael Salerno and Mathews Jacob
IEEE transactions on medical imaging, Vol.39(12), pp.3933-3943
12/2020
DOI: 10.1109/TMI.2020.3008329
PMCID: PMC7806246
PMID: 32746136
url
https://arxiv.org/pdf/1901.05542View
Open Access

Abstract

We introduce a kernel low-rank algorithm to recover free-breathing and ungated dynamic MRI from spiral acquisitions without explicit k-space navigators. It is often challenging for low-rank methods to recover free-breathing and ungated images from undersampled measurements; extensive cardiac and respiratory motion often results in the Casorati matrix not being sufficiently low-rank. Therefore, we exploit the non-linear structure of the dynamic data, which gives the low-rank kernel matrix. Unlike prior work that rely on navigators to estimate the manifold structure, we propose a kernel low-rank matrix completion method to directly fill in the missing k-space data from variable density spiral acquisitions. We validate the proposed scheme using simulated data and in-vivo data. Our results show that the proposed scheme provides improved reconstructions compared to the classical methods such as low-rank and XD-GRASP. The comparison with breath-held cine data shows that the quantitative metrics agree, whereas the image quality is marginally lower.
Navigation Magnetic Resonance Imaging Spirals Heuristic algorithms manifold models Image reconstruction non-ECG gated Storms Cardiac reconstruction cardiac MRI kernel methods free-breathing Kernel

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