Abstract
Medical image denoising is a very important and challenging area in the field of image processing. Magnetic resonance imaging is a very popular and most effective imaging technique. During the acquisition, MR images get affected by random noise which could be modeled as Gaussian or Rician distribution. In the past few decades, a wide variety of denoising techniques have been proposed. This paper presents a survey of advancements proposed for the denoising of magnetic resonance images. The performance of most significant image denoising domains has been analyzed qualitatively as well as quantitatively on the basis of mean square error and peak signal-to-noise ratio.
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