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41

DICTA
2003

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Adaptive Magnetic Resonance Image Denoising Using Mixture Model and Wavelet Shrinkage

14 years 8 days ago

Adaptive Magnetic Resonance Image Denoising Using Mixture Model and Wavelet Shrinkage

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Abstract. This paper proposes a new adaptive wavelet-based Magnetic Resonance images denoising algorithm. A Rician distribution for background-noise modelling is introduced and a Maximum-Likelihood method for the parameter estimation procedure is used. Further discrimination between edge- and noise-related coeﬃcients is achieved by updating the shrinkage function along consecutive scales and applying spatial constraints. The eﬃcacy of the algorithm is demonstrated on both simulated and real Magnetic Resonance images. The results is shown to be promising and outperform other denoising approaches.

Lei Jiang, Wenhui Yang

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	DICTA
Authors	Lei Jiang, Wenhui Yang

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