Deep Learning-based Image Reconstruction for High-Quality Medical Imaging: Developing deep learning models for image reconstruction in medical imaging modalities, improving image quality and diagnostic accuracy

Abstract

Deep learning has revolutionized medical imaging by significantly enhancing image reconstruction techniques. This paper presents a comprehensive review of deep learning-based image reconstruction methods in medical imaging modalities. The paper begins by discussing the limitations of traditional image reconstruction methods and the need for advanced techniques to improve image quality and diagnostic accuracy. It then provides an overview of deep learning and its applications in medical imaging. The main focus is on the development and implementation of deep learning models for image reconstruction, including convolutional neural networks (CNNs) and generative adversarial networks (GANs). The paper also discusses the challenges and future directions of deep learning-based image reconstruction in medical imaging.