Denoising MRI Medical Images using 3D Wavelet Transform

Magnetic resonance (MR) images are normally corrupted by random noise which makes the automatic feature extraction and analysis of clinical data complicated. Hence there is a necessity to denoise MR images for better analysis. Therefore, several denoising methods have been applied to improve MR image quality. Disadvantage of previous methods are reconstruction process is complicated and time consuming. This paper proposes a 3D extension of the wavelet transform (WT)-based bilateral filtering for Rician noise removal. Due to delineating capability of wavelet, 3D WT was employed to provide effective representation of the noisy coefficients. Bilateral filtering of the approximation coefficients in a modified neighborhood improves the de-noising efficiency and effectively preserved the relevant edge features. The subbands were processed with an enhanced Neigh Shrink thresholding algorithm. Validation was performed on both simulated and