DocumentCode
1423742
Title
Maximum-likelihood estimation of Rician distribution parameters
Author
Sijbers, Jan ; Den Dekker, Arnold J. ; Scheunders, Paul ; Van Dyck, Dirk
Author_Institution
Dept. of Phys., Antwerp Univ., Belgium
Volume
17
Issue
3
fYear
1998
fDate
6/1/1998 12:00:00 AM
Firstpage
357
Lastpage
361
Abstract
The problem of parameter estimation from Rician distributed data (e.g., magnitude magnetic resonance images) is addressed. The properties of conventional estimation methods are discussed and compared to maximum-likelihood (ML) estimation which is known to yield optimal results asymptotically. In contrast to previously proposed methods, ML estimation is demonstrated to be unbiased for high signal-to-noise ratio (SNR) and to yield physical relevant results for low SNR.
Keywords
biomedical NMR; medical image processing; parameter estimation; Rician distribution parameters; magnitude magnetic resonance images; maximum-likelihood estimation; medical diagnostic imaging; physical relevant results; signal-to-noise ratio; Gaussian noise; Image reconstruction; Magnetic resonance; Magnetic resonance imaging; Maximum likelihood estimation; Parameter estimation; Physics; Rician channels; Signal to noise ratio; Yield estimation; Computer Simulation; Likelihood Functions; Magnetic Resonance Imaging;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/42.712125
Filename
712125
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