Multi-Modal Medical Image Denoising using Wavelets: A Comparative Study

Author:

Patil* Rajesh1ORCID,Bhosale Surendra1ORCID

Affiliation:

1. Electrical Engineering Department, VJTI, Mumbai, India.

Abstract

In medical image processing Noise removal is an important step for recreating a high-quality image like X-ray, ultrasound, MRI etc. While acquiring, transmitting, and retrieving from storage devices normally images are degraded due to noises like Gaussian, Speckle etc. So, noise must be removed from the images for proper diagnosis. Researchers are still looking for an effective noise reduction means. Wavelet Transform (WT) is considered as a powerful transform method for removal of noise. For denoising of medical images affected by Gaussian noise, various wavelets have been proposed. In this paper, various wavelets are used to study the denoising multi-modal medical images affected by Gaussian noise. Here, proposed wavelet gives better results than the wavelets which have been implemented so far now. Denoising results of medical images are compared on the basis of Root Mean Square Error (RMSE), Signal-Noise Ratio (SNR), Peak Signal-Noise Ratio (PSNR) and execution time (TE).

Publisher

Oriental Scientific Publishing Company

Reference14 articles.

1. 1. Debashis Ganguly, Srabonti Chakraborty, Maricel Balitanas, and Tai-hoon Kim,” Medical Imaging: A Review” International Conference on Security-Enriched Urban Computing and Smart Grid, SUComS 2010

2. 2. Sugandha Agarwal, O.P. Singh and Deepak Nagaria, “Analysis and Comparison of Wavelet Transforms For Denoising MRI Image” Biomedical & Pharmacology Journal Vol. 10(2), 831-836 (2017)

3. 3. Mohd. Ameen, Shah Aqueel Ahmed, “An Extensive Review of Medical Image Denoising Techniques”, Global Journal of Medical Research: Radiology, Diagnostic Imaging and Instrumentation, Volume 16, Issue 2 Version 1.0, 2016

4. 4. Rajesh Patil, S. J. Bhosale, “Medical Image Denoising Techniques: A Review”, International Journal on Engineering, Science and Technology, Volume 4, No 1, 2022

5. 5. S. Kother Mohideen, Dr. S. Arumuga Perumal et al. (2008), “Image De-noising using Discrete Wavelet transform” , IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.1

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