Advanced Image Reconstruction Techniques Using Deep Learning for High-Quality Medical Applications: Develops deep learning models for image reconstruction in medical imaging modalities, improving image quality and diagnostic accuracy

Abstract

Deep learning has shown remarkable success in various medical imaging applications, including image reconstruction. This paper presents a comprehensive review and analysis of deep learning-based image reconstruction techniques for high-quality medical imaging. The primary focus is on the development and evaluation of deep learning models for improving image quality and diagnostic accuracy in medical imaging modalities. Various deep learning architectures, such as convolutional neural networks (CNNs) and generative adversarial networks (GANs), are discussed in detail, along with their applications in different medical imaging modalities. The paper also explores challenges, current trends, and future directions in this rapidly evolving field. Overall, deep learning-based image reconstruction holds great promise for enhancing medical imaging quality and facilitating more accurate diagnoses.