De-noising Medical Images Using Machine Learning, Deep Learning Approaches: A survey

(E-pub Ahead of Print)

Author(s): Ali Arshaghi*, Mohsen Ashourian, Leila Ghabeli

Journal Name: Current Medical Imaging
Formerly: Current Medical Imaging Reviews

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Abstract:

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

Methods: In this paper, a median filter algorithm will be modified and explain the image de-noising to wavelet transform and Non-local means (NLM), deep convolutional neural network (DnCNN) and Gaussian noise and Salt and pepper noise used in the medical skin image.

Results: PSNR values of CNN methods is higher and better than to others filters (Adaptive Wiener filter, Median filter and Adaptive Median filter, Wiener filter).

Conclusion: De-noising methods performance with indices SSIM, PSNR and MSE are tested and survey the result of simulation image de-noising.

Keywords: Medical de-noising, NLM, PSNR, image processing, CNN, Adaptive wiener filter

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1573405616666201118122908
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