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Journal of Electronic Imaging

Undersampling trajectory design for compressed sensing based dynamic contrast-enhanced magnetic resonance imaging
Author(s): Duan-Duan Liu; Dong Liang; Na Zhang; Xin Liu; Yuan-Ting Zhang
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Paper Abstract

Compressed sensing has the potential to address the challenge of simultaneously requiring high temporal and spatial resolution in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), by randomly undersampling the k-space with a predesigned trajectory. However, the traditional variable density (VD) design scheme includes inherent randomness since many probability density functions (PDFs) correspond to a given acceleration factor and one fixed PDF can generate different trajectories. This randomness may translate to an uncertainty in kinetic parameter estimation. We first evaluate how the one-to-many mapping in trajectory design influences DCE parameter estimation when high reduction factors are used. Then we propose a robust design scheme by adaptively segmenting k-space into low- and high-frequency domains considering the specific characteristics for different subjects and only applying the VD scheme in the high-frequency domain. Simulation results demonstrate high accuracy and robustness compared to the VD design.

Paper Details

Date Published: 20 January 2015
PDF: 10 pages
J. Electron. Imaging. 24(1) 013017 doi: 10.1117/1.JEI.24.1.013017
Published in: Journal of Electronic Imaging Volume 24, Issue 1
Show Author Affiliations
Duan-Duan Liu, The Chinese Univ. of Hong Kong (Hong Kong)
Dong Liang, Chinese Academy of Science (China)
Na Zhang, Chinese Academy of Science (China)
Xin Liu, Chinese Academy of Science (China)
Yuan-Ting Zhang, The Chinese Univ. of Hong Kong (Hong Kong)
Chinese Academy of Science (China)


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