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Adaptive SNR filtering technique for Rician noise denoising in MRI

Citation

Aarya, I and Jiang, D and Gale, T, Adaptive SNR filtering technique for Rician noise denoising in MRI, Proceedings of the 6th Biomedical Engineering International Conference (BMEiCON2013), 23-25 October 2013, Krabi, Thailand, pp. 6687669.23-29. ISBN 978-1-4799-1466-1 (2013) [Refereed Conference Paper]

Copyright Statement

Copyright 2013 IEEE

Official URL: http://dx.doi.org/10.1109/BMEiCon.2013.6687669

Abstract

MRI images are affected by Rician noise due to the magnitude image formation. Presence of Rician noise can significantly affect the image quality and contrast ratio of an image. In this paper we propose an adaptive filtering technique for Rician noise. Rician noise displays varying distribution characteristic depending on the SNR of the image. Based on the probability distribution function of noise and SNR information obtained from the image, the proposed filter uses local statistics of the neighborhood within the mask to perform denoising. The filter thus performs adaptive denoising based on the regional SNR of the neighborhood. The proposed filtering technique has been implemented on synthetic image and T2 weighted magnitude MRI images. The efficiency of the proposed filtering technique is verified with a study of the PSNR, MSSIM and RMSE characteristic of the denoised and noisy image with respect to the true image. The proposed denoising technique shows an improvement in the contrast ratio and PSNR of the noisy image.

Item Details

Item Type:Refereed Conference Paper
Keywords:adaptive filtering, denoising, MRI, Rayleigh noise, Rician noise
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Image Processing
Objective Division:Health
Objective Group:Health and Support Services
Objective Field:Diagnostic Methods
Author:Aarya, I (Miss Isshaa Aarya)
Author:Jiang, D (Dr Danchi Jiang)
Author:Gale, T (Dr Timothy Gale)
ID Code:88765
Year Published:2013
Deposited By:Engineering
Deposited On:2014-02-14
Last Modified:2017-11-18
Downloads:0

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