Conference proceeding
ACCURATE T2 MAPPING WITH SPARSITY AND LINEAR PREDICTABILITY FILTERING
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp.161-164
IEEE International Symposium on Biomedical Imaging
01/01/2014
DOI: 10.1109/ISBI.2014.6867834
Abstract
T2 mapping provides a quantitative manner to access tissue structure, composition, water content and iron levels. Nevertheless, due to the relative long scanning time, its practical usage is limited. This paper addresses this problem using a novel iterative nonlinear filtering method to achieve sparse sampling reconstruction. Specifically two filters are involved. One is the soft thresholding operator promoting spatial sparsity and temporal redundancy. The other is the Hankel matrix low-rank approximation enforcing the exponential structure along echo time dimension. The proposed method has been validated based on a brain T2 experiment data, and is shown to provide high image quality.
Details
- Title: Subtitle
- ACCURATE T2 MAPPING WITH SPARSITY AND LINEAR PREDICTABILITY FILTERING
- Creators
- Xi Peng - Shenzhen Inst Adv Technol, Paul C Lauterbur Res Ctr Biomed Imaging, Shenzhen, Guangdong, Peoples R ChinaLeslie Ying - University at Buffalo, State University of New YorkXin Liu - Shenzhen Institutes of Advanced TechnologyDong Liang - Shenzhen Institutes of Advanced Technology
- Resource Type
- Conference proceeding
- Publication Details
- 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp.161-164
- Publisher
- IEEE
- Series
- IEEE International Symposium on Biomedical Imaging
- DOI
- 10.1109/ISBI.2014.6867834
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Number of pages
- 4
- Grant note
- KQCX20120816155710259 / Shenzhen Peacock Plan 11301508; 61102043; 81120108012 / National Nature Science of Foundation of China; National Natural Science Foundation of China (NSFC) JC201104220219A / Basic Research Program of Shenzhen
- Language
- English
- Date published
- 01/01/2014
- Academic Unit
- Radiology
- Record Identifier
- 9984446262302771
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