Title: Identification and removal of different categories of noises from magnetic resonance image using hybrid partial differential equation-based filter

Authors: Ram Bharos Yadav; Subodh Srivastava; Rajeev Srivastava

Addresses: Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi-221005, UP, India ' Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi-221005, UP, India ' Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi-221005, UP, India

Abstract: This paper identifies various types of noise present into the MRI and filters them by choosing an appropriate filter. The different categories of noises during the acquisition of MR image may be generally corrupted due to external or internal causes. The external causes lead to an additive noise pattern which follows a Gaussian distribution (pdf). Causes of internal noise in MR image are basically the intrinsic noise that is generated during the acquisition process. Normally intrinsic noise in MR image follows the Rician distribution (pdf). The proposed filter gets adapted for the removal of specific types of noise based on SNR values of image data. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of PSNR, MSE, SSIM and CP. From the simulation results, it is observed that the proposed framework with CD-based prior is performing better in comparison to other priors.

Keywords: Gaussian noise reduction; Rician noise reduction; 2D MR images; Gaussian's probability distribution function; Rician's probability distribution function.

DOI: 10.1504/IJDSSS.2017.088050

International Journal of Digital Signals and Smart Systems, 2017 Vol.1 No.2, pp.87 - 98

Received: 27 May 2016
Accepted: 02 Feb 2017

Published online: 20 Nov 2017 *

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