Parallel generalized series MRI: Algorithm and application to cancer imaging

Dan Xu, Leslie Ying, Zhi-Pei Liang

Research output: Contribution to journalConference article

Abstract

MRI is a relatively slow imaging technique. Although imaging speeds have increased dramatically over the last three decades, many clinical and research applications, ranging from contrast-enhanced dynamic imaging of breast tumors to cardiac imaging, require still faster imaging methods. To address this problem, this paper presents a novel algorithm to integrate generalized series (GS) imaging with parallel imaging using multiple receiver coils. This algorithm takes advantage of both the conventional parallel data acquisition scheme and the GS model-based reduced-scan imaging method to achieve higher spatiotemporal resolution in dynamic imaging. The algorithm has been validated using both simulated and experimental data from dynamic contrast-enhanced MRI experiments, which produced excellent results. We expect the algorithm to be useful for a number of dynamic imaging applications, especially contrast-enhanced imaging of tumors.

Original languageEnglish (US)
Pages (from-to)1052-1055
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 II
StatePublished - Dec 1 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: Sep 1 2004Sep 5 2004

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Magnetic resonance imaging
Imaging techniques
Neoplasms
Breast Neoplasms
Tumors
Research
Data acquisition

ASJC Scopus subject areas

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

Cite this

Parallel generalized series MRI : Algorithm and application to cancer imaging. / Xu, Dan; Ying, Leslie; Liang, Zhi-Pei.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 26 II, 01.12.2004, p. 1052-1055.

Research output: Contribution to journalConference article

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