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

Content Provider	Springer Nature Link
Author	Sudeep, P. V. Palanisamy, P. Kesavadas, Chandrasekharan Sijbers, Jan Dekker, Arld J. Rajan, Jeny
Copyright Year	2016
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.
Starting Page	913
Ending Page	920
Page Count	8
File Format	PDF
ISSN	18631703
Journal	Signal, Image and Video Processing
Volume Number	11
Issue Number	5
e-ISSN	18631711
Language	English
Publisher	Springer London
Publisher Date	2016-12-24
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Denoising Magnetic resonance image Maximum likelihood estimation Noise Phase map Signal,Image and Speech Processing Image Processing and Computer Vision Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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