AI and Deep Learning in Medical Image Enhancement
*Corresponding Author: Dr. Andre Silva, Department of Image Processing, University of Luanda, Angola, Email: a.silva@postimg.aoReceived Date: Sep 03, 2025 / Published Date: Sep 30, 2025
Citation: Silva DA (2025) AI and Deep Learning in Medical Image Enhancement. J Radiol 14: 725.DOI: 10.4172/2167-7964.1000725
Copyright: © 2025 Dr. Andre Silva This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Abstract
This compilation examines the impact of artificial intelligence and deep learning on medical image post-processing. It highlights advancements in noise reduction, artifact removal, super-resolution, and image registration across modalities like CT, MRI, and ultrasound. The research explores the use of CNNs, GANs, and federated learning for enhanced image quality, dose reduction, and privacy preservation. Explainable AI and uncertainty quantification are emphasized for clinical trust and safety, alongside automated segmentation for diagnostic support. These developments promise improved accuracy and efficiency in medical imaging.
