Under-sampling trajectory design for compressed sensing MRI

Duan-Duan Liu, Dong Liang*, Xin Liu, Yuan-Ting Zhang

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

24 Citations (Scopus)

Abstract

The under-sampling trajectory design plays a key role in compressed sensing MRI. The traditional design scheme using probability density function (PDF) is based up observation on energy distribution in k-space rather than systematic optimization, which results in non-deterministic trajectory even with a fixed PDF. Guidance-based method like Bayesian inference scheme is always bothered with high computational complexity on entropy. In this paper, we study how to adaptively design an under-sampling trajectory in the context of CS with systematic optimization and small complexity. Simulation results conducted on images from different slices and dynamic sequence demonstrate the effectiveness of the proposed method by comparing the designed trajectory with those by traditional method. © 2012 IEEE.
Original languageEnglish
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages73-76
ISBN (Electronic)9781457717871
DOIs
Publication statusPublished - Aug 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2012) - San Diego, United States
Duration: 28 Aug 20121 Sept 2012

Publication series

NameIEEE Engineering in Medicine and Biology Society Conference Proceedings
PublisherIEEE
ISSN (Print)1557-170X

Conference

Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2012)
Abbreviated titleEMBC 2012
PlaceUnited States
CitySan Diego
Period28/08/121/09/12

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