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Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI
Joint Authors
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-12
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
It is challenging and inspiring for us to achieve high spatiotemporal resolutions in dynamic cardiac magnetic resonance imaging (MRI).
In this paper, we introduce two novel models and algorithms to reconstruct dynamic cardiac MRI data from under-sampled k - t space data.
In contrast to classical low-rank and sparse model, we use rank-one and transformed sparse model to exploit the correlations in the dataset.
In addition, we propose projected alternative direction method (PADM) and alternative hard thresholding method (AHTM) to solve our proposed models.
Numerical experiments of cardiac perfusion and cardiac cine MRI data demonstrate improvement in performance.
American Psychological Association (APA)
Xiu, Xianchao& Kong, Lingchen. 2015. Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI. BioMed Research International،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1054470
Modern Language Association (MLA)
Xiu, Xianchao& Kong, Lingchen. Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI. BioMed Research International No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1054470
American Medical Association (AMA)
Xiu, Xianchao& Kong, Lingchen. Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1054470
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1054470