T2 prime mapping from highly undersampled data using compressed sensing with patch based low rank penalty

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In magnetic resonance (MR) imaging, T2 and T2 star (T2∗) relaxation times represent tissue properties, which can be quantified by specific imaging sequences. Especially, T2 prime (T2′) that can be derived from T2 and T2∗ are clinically valuable for delineation of areas with increased oxygen extraction fraction in acute stroke. However, there are limitations in this method because it requires acquisition of many images for the generation of T2 and T2∗ relaxation time maps. In particular, time saving is the most important factor in acquisition of MRI in acute ischemic stroke because therapy should be given to patients as soon as possible. Therefore, to reduce the acquisition time of MR data, we use a compressed sensing algorithm using patch based low rank penalty for the reconstruction of T2 and T2∗ weighted images to obtain the T2 prime map. Our results showed that significant acceleration in T2′ image acquisition is possible using the proposed method.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Issue Date
2014-04
Language
English
Citation

2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, pp.645 - 648

ISSN
1945-7928
DOI
10.1109/isbi.2014.6867953
URI
http://hdl.handle.net/10203/314012
Appears in Collection
BiS-Conference Papers(학술회의논문)AI-Conference Papers(학술대회논문)
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