Conference proceeding
PARALLEL IMAGING VIA SPARSE REPRESENTATION OVER A LEARNED DICTIONARY
2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), Vol.2015-, pp.687-690
IEEE International Symposium on Biomedical Imaging
04/01/2015
DOI: 10.1109/ISBI.2015.7163966
Abstract
This paper proposes an adaptive reconstruction method for parallel imaging (PI) via sparse representation over a learned dictionary and also a corresponding dictionary learning based PI (DL-PI) algorithm. DL-PI adopts the "divide and conquer" strategy to solve the l(2)-DL reconstruction formulation, with dictionary learning to capture the structure information and a Taylor approximation to update the target image analytically. The proposed approach has been applied to parallel magnetic resonance imaging (MRI) and compared to two latest state-of-the-art methods. The experimental results on in-vivo data show that the DL-PI algorithm possesses strong ability in detail preservation and is competent in artifact removal during the MR image reconstruction process.
Details
- Title: Subtitle
- PARALLEL IMAGING VIA SPARSE REPRESENTATION OVER A LEARNED DICTIONARY
- Creators
- Shanshan Wang - Chinese Acad Sci, SIAT, Paul C Lauterbur Res Ctr Biomed Imaging, Shenzhen, Peoples R ChinaXi Peng - Chinese Acad Sci, SIAT, Paul C Lauterbur Res Ctr Biomed Imaging, Shenzhen, Peoples R ChinaPei Dong - University of SydneyLeslie Ying - State University of New YorkDavid Dagan Feng - University of SydneyDong Liang - Chinese Acad Sci, SIAT, Paul C Lauterbur Res Ctr Biomed Imaging, Shenzhen, Peoples R China
- Resource Type
- Conference proceeding
- Publication Details
- 2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), Vol.2015-, pp.687-690
- Publisher
- IEEE
- Series
- IEEE International Symposium on Biomedical Imaging
- DOI
- 10.1109/ISBI.2015.7163966
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Number of pages
- 4
- Language
- English
- Date published
- 04/01/2015
- Academic Unit
- Radiology
- Record Identifier
- 9984446456202771
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