Conference proceeding
Accelerated image reconstruction with separable Hankel regularization in parallel MRI
2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), Vol.2021, pp.3403-3406
IEEE Engineering in Medicine and Biology Society Conference Proceedings
11/2021
DOI: 10.1109/EMBC46164.2021.9629962
PMID: 34891970
Abstract
Magnetic resonance imaging has been widely adopted in clinical diagnose, however, it suffers from relatively long data acquisition time. Sparse sampling with reconstruction can speed up the data acquisition duration. As the state-of-the-art magnetic resonance imaging methods, the structured low rank reconstruction approaches embrace the advantage of holding low reconstruction errors and permit flexible undersampling patterns. However, this type of method demands intensive computations and high memory consumptions, thereby resulting in a lengthy reconstruction time. In this work, we proposed a separable Hankel low rank reconstruction method to explore the low rankness of each row and each column. Furthermore, we utilized the self-consistence and conjugate symmetry property of k-space data. The experimental results demonstrated that the proposed method outperforms the state-of-the-art approaches in terms of lower reconstruction errors and better detail preservation. Besides, the proposed method requires much less computation and memory consumption.
Details
- Title: Subtitle
- Accelerated image reconstruction with separable Hankel regularization in parallel MRI
- Creators
- Xinlin Zhang - Xiamen UniversityZi Wang - Xiamen UniversityXi Peng - Mayo Clin, Dept Radiol, Rochester, MN 55902 USAQin Xu - NeusoftDi Guo - Xiamen University of TechnologyXiaobo Qu - Xiamen University
- Resource Type
- Conference proceeding
- Publication Details
- 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), Vol.2021, pp.3403-3406
- Publisher
- IEEE
- Series
- IEEE Engineering in Medicine and Biology Society Conference Proceedings
- DOI
- 10.1109/EMBC46164.2021.9629962
- PMID
- 34891970
- ISSN
- 1557-170X
- eISSN
- 1558-4615
- Number of pages
- 4
- Grant note
- 2017YFC0108703 / National Key R&D Program of China 61971361; 61871341; 61811530021; U1632274 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) XDHT2021004C / China Mobile Communications Group Fujian Co., Ltd. Xiamen Branch Project 2019-WJ-31 / Health Education Joint Project of Fujian Province Xiamen University Nanqiang Outstanding Talents Program
- Language
- English
- Date published
- 11/2021
- Academic Unit
- Radiology
- Record Identifier
- 9984446062002771
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