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Magnetic Resonance Imaging Rician Noise Reduction using Advance Wavelet Transform and Nonlocal Mean Filter

Ravi Boda, B Rajendra Naik


MR imaging is a powerful medical imaging modality for visualizing soft tissues of human body. However, while acquisition of image Magnetic resonance imaging machine adds noise, which degrades the quality of image. Time averaging of any medical images aimed at increasing the Highest Signal to Noise Percentage would leads to extra acquisition time and decreases the spatial resolution. Therefore, Noise reduction need to be performed in order to rise the image feature for more perfect analysis. The goal of proposed noise reduction process is to find good approximation of true image from noisy image. The Rician noise reduction is done using two stage processes, first modified Wavelet Transform is applied which works on based sparseness of image and then Rotational invariant version of Non-Local Mean filter is applied (similar patches will gain high weight as compared to the dissimilar patches). The performance evolution is done using PSNR and Image Structural Match Measure. The anticipated work shows superior performance as compared to conventional noise reduction methods.


Modified Wavelet Transform, Non-Local Mean filter (NLM), PSNR, Image Structural Match Measure (ISMM).

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