Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …

Advances in artificial intelligence-based methods have led to the development and
publication of numerous systems for auto-segmentation in radiotherapy. These systems …

Background and purpose Delineating organs at risk (OARs) on computed tomography (CT)
images is an essential step in radiation therapy; however, it is notoriously time-consuming …

In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …

Manual segmentation of target structures and organs at risk is a crucial step in the
radiotherapy workflow. It has the disadvantages that it can require several hours of clinician …

Radiation therapy treatments are typically planned based on a single image set, assuming
that the patient's anatomy and its position relative to the delivery system remains constant …

Lung cancer is the leading cause of cancer-related mortality for males and females.
Radiation therapy (RT) is one of the primary treatment modalities for lung cancer. While …

Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck
(H&N), which requires a precise spatial description of the target volumes and organs at risk …

Background and purpose In radiotherapy, automatic organ-at-risk segmentation algorithms
allow faster delineation times, but clinically relevant contour evaluation remains challenging …

Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …