Medical image reconstruction aims to acquire high-quality medical images for clinical usage
at minimal cost and risk to the patients. Deep learning and its applications in medical …

Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT)
is a mathematical process that generates images at many different angles around the …

Medical imaging is an invaluable resource in medicine as it enables to peer inside the
human body and provides scientists and physicians with a wealth of information …

Machine learning techniques are essential components of medical imaging research.
Recently, a highly flexible machine learning approach known as deep learning has …

Deep learning technologies and applications demonstrate one of the most important
upcoming developments in radiology. The impact and influence of these technologies on …

Compared with common deep learning methods (eg, convolutional neural networks),
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …

Background To review and evaluate approaches to convolutional neural network (CNN)
reconstruction for accelerated cardiac MR imaging in the real clinical context. Methods Two …

The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …

Medical imaging is crucial in modern clinics to provide guidance to the diagnosis and
treatment of diseases. Medical image reconstruction is one of the most fundamental and …