Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …

This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …

The field of medical image reconstruction has seen roughly four types of methods. The first
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …

This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …

In this paper we describe an investigation into the application of deep learning methods for
low-dose and sparse angle computed tomography using small training datasets. To motivate …

Objectives Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and
quantitative assessment of lung morphometry, but its long acquisition time is not well …

Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …

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

Image processing plays a crucial role in maximising diagnostic quality of positron emission
tomography (PET) images. Recently, deep learning methods developed across many fields …

We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic
resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for …