Robust phase sensitive inversion recovery imaging using a Markov random field model

Ravindra M. Garach, Jim Ji, Lei Ying, Jingfei Ma

Research output: Contribution to journalArticle

Abstract

This paper presents a novel method for phase sensitive inversion recovery (PSIR) imaging for improved T1 contrast. This method models the phase of the complex magnetic resonance image using a statistical model based on Markov Random Fields. A computationally efficient optimization method is developed. Computer simulations and in-vivo brain imaging experiments show that the proposed method can produce PSIR images with enhanced T1 contrast and it is robust against high levels of data noise even when rapid phase variations are presented.

Original languageEnglish
Pages (from-to)1569-1572
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 II
Publication statusPublished - 2004
Externally publishedYes

Fingerprint

Imaging techniques
Recovery
Magnetic resonance
Brain
Computer simulation
computer simulation
brain
Experiments
method
inversion
experiment
Statistical Models

Keywords

  • Inversion recovery
  • Magnetic resonance imaging
  • Markov random field
  • Optimization
  • Phase sensitive inversion recovery

ASJC Scopus subject areas

  • Bioengineering

Cite this

Robust phase sensitive inversion recovery imaging using a Markov random field model. / Garach, Ravindra M.; Ji, Jim; Ying, Lei; Ma, Jingfei.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 26 II, 2004, p. 1569-1572.

Research output: Contribution to journalArticle

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