A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI

M. Usman, C. Prieto, F. Odille, D. Atkinson, T. Schaeffter, P. G. Batchelor

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved.
Original languageEnglish
Pages (from-to)N99 - N114
Number of pages16
JournalPhysics in Medicine and Biology
Issue number7
Early online date2 Mar 2011
Publication statusPublished - 7 Apr 2011


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