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A Review on Magnetic Resonance Images Denoising Techniques

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Machine Intelligence and Signal Analysis

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 748))

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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Authors and Affiliations

  1. MANIT, Bhopal, Madhya Pradesh, India

    Abhishek Sharma & Vijayshri Chaurasia

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  1. Abhishek Sharma
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  2. Vijayshri Chaurasia
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Correspondence to Abhishek Sharma .

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Editors and Affiliations

  1. Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    M. Tanveer

  2. Discipline of Electrical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    Ram Bilas Pachori

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Sharma, A., Chaurasia, V. (2019). A Review on Magnetic Resonance Images Denoising Techniques. In: Tanveer, M., Pachori, R. (eds) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, vol 748. Springer, Singapore. https://doi.org/10.1007/978-981-13-0923-6_60

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