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

被引:4
|
作者
Arshaghi, Ali [1 ]
Ashourian, Mohsen [2 ]
Ghabeli, Leila [1 ]
机构
[1] Islamic Azad Univ, Cent Tehran Branch, Dept Elect Engn, Tehran, Iran
[2] Islamic Azad Univ, Majlesi Branch, Dept Elect Engn, Esfahan, Iran
关键词
Medical denoising; NLM; PSNR; image processing; CNN; adaptive wiener filter; WAVELET; TRANSFORM; CURVELET;
D O I
10.2174/1573405616666201118122908
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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 (D n-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.
引用
收藏
页码:578 / 594
页数:17
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