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Denoising Medical Images Using Machine Learning, Deep Learning Approaches: A Survey

[ Vol. 17 , Issue. 5 ]

Author(s):

Ali Arshaghi , Mohsen Ashourian* and Leila Ghabeli   Pages 578 - 594 ( 17 )

Abstract:


Objective: Several denoising methods for medical images have been applied, such as Wavelet Transform, CNN, linear and Non-linear methods.

Methods: In this paper, A median filter algorithm will be modified and the image denoising method to wavelet transform and Non-local means (NLM), deep convolutional neural network (Dn- CNN), Gaussian noise, and Salt and pepper noise used in the medical image is explained.

Results: PSNR values of the CNN method are higher and showed better results than different filters (Adaptive Wiener filter, Median filter, and Adaptive Median filter, Wiener filter).

Conclusion: Denoising methods performance with indices SSIM, PSNR, and MSE have been tested, and the results of simulation image denoising are also presented in this article.

Keywords:

Medical denoising, NLM, PSNR, image processing, CNN, adaptive wiener filter.

Affiliation:

Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Department of Electrical Engineering, Majlesi Branch, Islamic Azad University, Isfahan, Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran

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