A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

P. V. Sudeep*, P. Palanisamy, Chandrasekharan Kesavadas, Jan Sijbers, Arnold J. Den Dekker, Jeny Rajan

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
98 Downloads (Pure)

Abstract

A phase map can be obtained from the real and imaginary components of a complex valued magnetic resonance (MR) image. Many applications, such as MR phase velocity mapping and susceptibility mapping, make use of the information contained in the MR phase maps. Unfortunately, noise in the complex MR signal affects the measurement of parameters related to phase (e.g, the phase velocity). In this paper, we propose a nonlocal maximum likelihood (NLML) estimation method for enhancing phase maps. The proposed method estimates the true underlying phase map from a noisy MR phase map. Experiments on both simulated and real data sets indicate that the proposed NLML method has a better performance in terms of qualitative and quantitative evaluations when compared to state-of-the-art methods.

Original languageEnglish
Pages (from-to)913-920
JournalSignal, Image and Video Processing
Volume11
Issue number5
DOIs
Publication statusPublished - 2017

Bibliographical note

Accepted Author Manuscript

Keywords

  • Denoising
  • Magnetic resonance image
  • Maximum likelihood estimation
  • Noise
  • Phase map

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