A Proposed Framework to Denoise the Medical Images using Deep Learning Techniques
Year: 2024
Type: article
Abstract: Image Denoising has become a promising task nowadays in the domain of Image processing. Throughout this paper, a complete analysis of all the methods of Image Denoising has been studied. In this paper, medical image dataset which include Chest X-ray images of a patient has been taken into consideration. Numerous deep learning methods including Convolutional Neural Networks and Denoising Autoencoder have been discussed here. Chest X-ray images has been denoised first using a Denoising Autoencoder and then a Convolutional Neural network is implemented with a U-Net structure. A number of performance evaluation metrics have been employed to assess the quality of denoised images, such as SSIM (Structural Similarity Index) and PSNR (Peak Signal to Noise Ratio). A comparison of all the methods has been done in a tabular format. Later the conclusion and future scope of this paper has been discussed.
Authors: Das, Suchismita, Khan, Noor-A-Nabi
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6968214533
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