A Review of Rician Noise Reduction in MRI Images using Wave Atom Transform

Magnetic resonance imaging is a medical imaging technique that measures the response of atomic nuclei of body tissues to high frequency radio waves when placed in a strong magnetic field and that produces images of the internal organs. De-noising is always a challenging problem in magnetic resonance imaging and important for clinical diagnosis and computerized analysis, such as tissue classification and segmentation. It is well known that the noise in magnetic resonance imaging has a Rician distribution. . In this paper, an improved de-noising technique is proposed on Magnetic Resonance Images highly corrupted with Rician Noise using wave atom shrinkage. General Terms Clinical diagnosis, tissue classification, segmentation

[1]  Robert D. Nowak,et al.  Wavelet-based Rician noise removal for magnetic resonance imaging , 1999, IEEE Trans. Image Process..

[2]  Gerlind Plonka-Hoch,et al.  Nonlinear Regularized Reaction-Diffusion Filters for Denoising of Images With Textures , 2008, IEEE Transactions on Image Processing.

[3]  R. S. Moni,et al.  Noise Reduction in Magnetic Resonance Images using Wave Atom Shrinkage , 2010 .

[4]  L D Cromwell,et al.  Filtering noise from images with wavelet transforms , 1991, Magnetic resonance in medicine.

[5]  J.B.T.M. Roerdink,et al.  A review of wavelet denoising in MRI and ultrasound brain imaging , 2006 .

[6]  M. Dylan Tisdall,et al.  MRI denoising via phase error estimation , 2005, SPIE Medical Imaging.

[7]  Cheng Guan Koay,et al.  Analytically exact correction scheme for signal extraction from noisy magnitude MR signals. , 2006, Journal of magnetic resonance.

[8]  G. Cottet,et al.  Image processing through reaction combined with nonlinear diffusion , 1993 .

[9]  J. Sijbers,et al.  Automatic estimation of the noise variance from the histogram of a magnetic resonance image , 2007, Physics in medicine and biology.

[10]  J. Hogg.  Magnetic resonance imaging. , 1994, Journal of the Royal Naval Medical Service.

[11]  L. Demanet,et al.  Wave atoms and sparsity of oscillatory patterns , 2007 .

[12]  Jos B. T. M. Roerdink,et al.  Denoising functional MR images: a comparison of wavelet denoising and Gaussian smoothing , 2004, IEEE Transactions on Medical Imaging.

[13]  J. Rajeesh,et al.  Rician noise removal on MRI using wave atom transform with histogram based noise variance estimation , 2010, 2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES.

[14]  Jacques A. de Guise,et al.  A method for modeling noise in medical images , 2004, IEEE Transactions on Medical Imaging.