Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is
practised. AI platforms excel in recognizing complex patterns in medical data and provide a …

Manual image segmentation is a time-consuming task routinely performed in radiotherapy to
identify each patient's targets and anatomical structures. The efficacy and safety of the …

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 …

Abstract Purpose Cancer-associated fibroblasts (CAFs) expressing fibroblast activation
protein (FAP) have been associated with the aggressive nature of head and neck cancers …

Radiation therapy is one of the most widely used therapies for cancer treatment. A critical
step in radiation therapy planning is to accurately delineate all organs at risk (OARs) to …

Machine learning approaches to problem-solving are growing rapidly within healthcare, and
radiation oncology is no exception. With the burgeoning interest in machine learning comes …

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 …

Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …

Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …

Segmentation of organs and structures, as either targets or organs‐at‐risk, has a significant
influence on the success of radiation therapy. Manual segmentation is a tedious and time …