منابع مشابه
Estimation of the noise in magnitude MR images.
Magnitude magnetic resonance data are Rician distributed. In this note a new method is proposed to estimate the image noise variance for this type of data distribution. The method is based on a double image acquisition, thereby exploiting the knowledge of the Rice distribution moments.
متن کاملOn the Expectation-Maximization algorithm for Rice-Rayleigh mixtures with application to noise parameter estimation in magnitude MR datasets
Magnitude magnetic resonance (MR) images are noise-contaminated measurements of the true signal, and it is important to assess the noise in many applications. A recently introduced approach models the magnitude MR datum at each voxel in terms of a mixture of upto one Rayleigh and an a priori unspecified number of Rice components, all with a common noise parameter. The Expectation-Maximization (...
متن کاملParameter estimation from magnitude MR images
This article deals with the estimation of model-based parameters, such as the noise variance and signal components, from magnitude magnetic resonance (MR) images. Special attention has been paid to the estimation of T1and T2-relaxation parameters. It is shown that most of the conventional estimation methods, when applied to magnitude MR images, yield biased results. Also, it is shown how the kn...
متن کاملAdaptive anisotropic noise filtering for magnitude MR data.
Conventional noise filtering schemes applied to magnitude magnetic resonance (MR) images tacitly assume Gauss distributed noise. Magnitude MR data, however, are Rice distributed. Not incorporating this knowledge leads inevitably to biased results, in particular when applying such filters in regions with low signal-to-noise ratio. In this work, we show how the Rice data probability distribution ...
متن کاملAdaptive anisotropic noise ltering for magnitude MR data
Conventional noise ltering schemes applied to magnitude magnetic resonance (MR) images tacitly assume Gauss distributed noise. Magnitude MR data, however, are Rice distributed. Not incorporating this knowledge leads inevitably to biased results, in particular when applying such lters in regions with low signal-to-noise ratio. In this work, we show how the Rice data probability distribution can ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Medical Imaging
سال: 2009
ISSN: 0278-0062,1558-254X
DOI: 10.1109/tmi.2009.2024415