@inproceedings{bb3fe7b6853c4e268e4f8c21a6c1e4fa,
title = "Compressed-sensing dynamic MR imaging with partially known support",
abstract = "Compressed Sensing (CS) has recently been applied to dynamic MRI to improve the acquisition speed. Existing methods exploit the information that the dynamic images are sparse in the spatial and temporal-frequency (y-f) domain. In this paper, we propose to use the additional prior information in CS reconstruction that the support of y-f space is partially known from the motion pattern of dynamic MR images. The reconstruction is then formulated as a truncated ℓ1 minimization problem. Experimental results show that the dynamic image reconstruction quality of the proposed method is superior to that of existing methods when the same number of measurements is used.",
keywords = "Compressed Sensing, Dynamic MRI, Partially Known Support, Truncated ℓ Minimization",
author = "Dong Liang and Leslie Ying",
year = "2010",
doi = "10.1109/IEMBS.2010.5626077",
language = "English",
isbn = "9781424441235",
series = "2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10",
pages = "2829--2832",
booktitle = "2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10",
note = "2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 ; Conference date: 31-08-2010 Through 04-09-2010",
}