Deep Learning-based Medical Image Reconstruction for Improved Diagnostics: Implementing deep learning techniques for reconstructing medical images to improve diagnostic accuracy

Abstract

This research paper explores the application of deep learning techniques in medical image reconstruction to enhance diagnostic accuracy. Medical imaging plays a crucial role in modern healthcare, aiding in the diagnosis and treatment of various medical conditions. Traditional image reconstruction methods often suffer from limitations such as long processing times and suboptimal image quality. Deep learning has emerged as a promising approach to address these challenges, offering the potential to improve image reconstruction speed and quality. This paper presents a comprehensive review of deep learning-based medical image reconstruction techniques, discussing their strengths, limitations, and future directions. We also provide a comparative analysis of existing approaches and highlight key areas for further research and development.