@inproceedings{bfe0e4932a754917900379f61ae52d1c,
title = "Low rank matrix recovery for real-time cardiac MRI",
abstract = "Real-time cardiac MRI is a very challenging problem because of limitations on imaging speed and resolution. To address this problem, the (k,t) - space MR signal is modeled as being partially separable along the spatial and temporal dimensions, which results in a rank-deficient data matrix. Image reconstruction is then formulated as a low-rank matrix recovery problem, which is solved using emerging low-rank matrix recovery techniques. In this paper, the PowerFactorization algorithm is applied to efficiently recover the cardiac data matrix. Promising results are presented to demonstrate the performance of this novel approach.",
keywords = "Compressed sensing, Dynamic MRI, Low-rank matrices, Matrix recovery, Spatiotemporal modeling",
author = "Bo Zhao and Haldar, {Justin P.} and Cornelius Brinegar and Zhi-Pei Liang",
year = "2010",
doi = "10.1109/ISBI.2010.5490156",
language = "English (US)",
isbn = "9781424441266",
series = "2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings",
pages = "996--999",
booktitle = "2010 7th IEEE International Symposium on Biomedical Imaging",
note = "7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 ; Conference date: 14-04-2010 Through 17-04-2010",
}