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Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
by
Nagpal, Prashant
, Mathews, Jacob
, Zhou, Ruixi
, Salerno, Michael
, Ahmed, Abdul Haseeb
, Yang, Yang
in
Algorithms
/ Blurring
/ Breathing
/ Data acquisition
/ Image reconstruction
/ Iterative algorithms
/ Kernels
/ Manifolds
/ Navigators
/ Regularization
/ State of the art
2020
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Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
by
Nagpal, Prashant
, Mathews, Jacob
, Zhou, Ruixi
, Salerno, Michael
, Ahmed, Abdul Haseeb
, Yang, Yang
in
Algorithms
/ Blurring
/ Breathing
/ Data acquisition
/ Image reconstruction
/ Iterative algorithms
/ Kernels
/ Manifolds
/ Navigators
/ Regularization
/ State of the art
2020
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Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
by
Nagpal, Prashant
, Mathews, Jacob
, Zhou, Ruixi
, Salerno, Michael
, Ahmed, Abdul Haseeb
, Yang, Yang
in
Algorithms
/ Blurring
/ Breathing
/ Data acquisition
/ Image reconstruction
/ Iterative algorithms
/ Kernels
/ Manifolds
/ Navigators
/ Regularization
/ State of the art
2020
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Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
Paper
Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
2020
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Overview
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.
Publisher
Cornell University Library, arXiv.org
Subject
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