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 …

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 …

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 …

Background: The future of artificial intelligence (AI) heralds unprecedented change for the
field of radiation oncology. Commercial vendors and academic institutions have created AI …

Treatment planning is an essential step of the radiotherapy workflow. It has become more
sophisticated over the past couple of decades with the help of computer science, enabling …

Treatment planning plays an important role in the process of radiotherapy (RT). The quality
of the treatment plan directly and significantly affects patient treatment outcomes. In the past …

Abstract Machine learning technology has a growing impact on radiation oncology with an
increasing presence in research and industry. The prevalence of diverse data including 3D …

Artificial intelligence, and in particular deep learning using convolutional neural networks,
has been used extensively for image classification and segmentation, including on medical …

Machine learning (ML) has the potential to revolutionize the field of radiation oncology, but
there is much work to be done. In this article, we approach the radiotherapy process from a …

Artificial intelligence (AI) has already been implemented widely in the medical field in the
recent years. This paper first reviews the background of AI and radiotherapy. Then it …