The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Introduction: Deep Learning (DL) is a machine learning technique that uses deep neural
networks to create a model. The application areas of deep learning in radiation oncology …

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data
processing techniques. One such technique, deep learning (DL), has become a remarkably …

Deep learning (DL) approaches are part of the machine learning (ML) subfield concerned
with the development of computational models to train artificial intelligence systems. DL …

The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in
combination with other methods. The planning and delivery of radiotherapy treatment is a …

Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

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

Abstract The advent of Deep Learning (DL) is poised to dramatically change the delivery of
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …

The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …