Litcius/Paper detail

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

Ali Arshaghi, Mohsen Ashourian, Leila Ghabeli

2020Current Medical Imaging Formerly Current Medical Imaging Reviews14 citationsDOI

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.

Topics & Concepts

Artificial intelligenceNoise reductionWiener filterComputer sciencePattern recognition (psychology)Non-local meansFilter (signal processing)Gaussian filterConvolutional neural networkSalt-and-pepper noiseWavelet transformComputer visionMedian filterNoise (video)Adaptive filterWaveletMathematicsImage denoisingImage (mathematics)Image processingAlgorithmImage and Signal Denoising MethodsBrain Tumor Detection and ClassificationAdvanced Technologies and Applied Computing