A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps
P. V. Sudeep (National Institute of Technology Karnataka, National Institute of Technology - Tiruchirappalli)
P. Palanisamy (National Institute of Technology - Tiruchirappalli)
Chandrasekharan Kesavadas (Sree Chitra Tirunal Institute for Medical Sciences and Technology)
Jan Sijbers (Universiteit Antwerpen)
AJ den Dekker (Universiteit Antwerpen, TU Delft - Team Michel Verhaegen)
Jeny Rajan (National Institute of Technology Karnataka)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
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.