Undersampling trajectory design for compressed sensing based dynamic contrast-enhanced magnetic resonance imaging
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AbstractCompressed 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.
All Author(s) ListLiu D.-D., Liang D., Zhang N., Liu X., Zhang Y.-T.
Journal nameJournal of Electronic Imaging
Year2015
Month1
Day1
Volume Number24
Issue Number1
PublisherS P I E - International Society for Optical Engineering
Place of PublicationUnited States
ISSN1017-9909
eISSN1560-229X
LanguagesEnglish-United Kingdom
KeywordsCompressed sensing, DCE-MRI, Undersampling trajectory design

Last updated on 2020-29-11 at 02:30