Rapid free-breathing dynamic contrast-enhanced MRI using motion-resolved compressed sensing

Li Feng, Daniel K. Sodickson, Ricardo Otazo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Compressed sensing is a powerful rapid imaging approach for Magnetic Resonance Imaging (MRI) and has been applied to many clinical applications. In this work, we propose a new use of sparsity in addition to speed. In particular, we present a novel way of handling respiratory motion using compressed sensing for dynamic contrast-enhanced MRI. The proposed technique, called XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel MRI), sorts the continuously acquired radial k-space data into undersampled contrast phases at multiple respiratory motion states using the self-navigation properties of radial imaging and employs a multidimensional compressed sensing reconstruction to exploit sparsity along both contrast-enhancement and respiratory motion dimensions. XD-GRASP improves image quality and also enables to track respiratory motion during contrast enhancement, which can potentially be of clinical value.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Pages889-892
Number of pages4
ISBN (Electronic)9781479923748
DOIs
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2015-July
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States
CityBrooklyn
Period4/16/154/19/15

Keywords

  • Compressed sensing
  • free-breathing imaging
  • golden-angle radial sampling
  • motion compensation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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