Channel reduction in massive array parallel MRI.

Shuo Feng, Jim Ji

Research output: Contribution to journalArticle

Abstract

This paper presents a method to explore the flexibility of channel reduction in k-domain parallel imaging with massive arrays to improve the computation efficiency. MCMLI and GRAPPA are k-domain reconstruction methods that use a neighborhood of PE columns, FE line(s) and all channels in the interpolation kernels. For massive array which contains a large number of element coils computation cost can be a significant problem. In this paper, channel selection and reduction is performed according to the correlation between channel images for individual channel reconstructions. Simulation results show that the proposed channel reduction algorithm can achieve similar or improved reconstruction quality with significantly reduced computation for massive arrays with localized sensitivity.

Original languageEnglish
Pages (from-to)4045-4048
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Publication statusPublished - 2009
Externally publishedYes

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Magnetic resonance imaging
Costs and Cost Analysis
Interpolation
Imaging techniques
interpolation
Costs
cost
simulation
method

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

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