@inproceedings{4e5fea83ee3149cb83986b02de1786f7,
title = "Accelerating cardiovascular imaging by exploiting regional low-rank structure via group sparsity",
abstract = "Sparse sampling of (k, t)-space has proved useful for cardiac MRI. This paper builds on previous work on using partial separability (PS) and spatial-spectral sparsity for high-quality image reconstruction from highly undersampled (k, t)-space data. This new method uses a more flexible control over the PS-induced low-rank constraint via group-sparse regularization. A novel algorithm is also described to solve the corresponding (1,2)-norm regularized inverse problem. Reconstruction results from simulated cardiovascular imaging data are presented to demonstrate the performance of the proposed method.",
keywords = "Cardiovascular MRI, Group sparsity, Inverse problems, Low-rank modeling, Partial separability",
author = "Christodoulou, {Anthony G.} and Babacan, {S. Derin} and Liang, {Zhi Pei}",
year = "2012",
doi = "10.1109/ISBI.2012.6235551",
language = "English (US)",
isbn = "9781457718588",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "330--333",
booktitle = "2012 9th IEEE International Symposium on Biomedical Imaging",
note = "2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 ; Conference date: 02-05-2012 Through 05-05-2012",
}