Abstract
Presence of noise in medical images leads to loss in the visual information available and may lead to false analysis by medical experts. Major sources include the noise generated due to handheld devices. Recent trend towards low dose imaging also increases the noise in the images. The decrease of noise in medical images is required for higher accuracy. So, Convolution neural network (CNN) are used for the denoising of images. De-noising using CNN based methods is viable and workable. This paper reviews the latest generative adversarial network (GAN) based medical image denoising algorithms. Challenges and future scope are also discussed. This study shall help new researchers to understand the recent trends and algorithms in image denoising for medical images.
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