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 …

Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT)
and their integration into modern software-based systems raise new challenges to the …

Background: Over half a million individuals are diagnosed with head and neck cancer each
year globally. Radiotherapy is an important curative treatment for this disease, but it requires …

Purpose Radiation therapy treatment planning is a time‐consuming and iterative manual
process. Consequently, plan quality varies greatly between and within institutions. Artificial …

Advances in computing hardware and software platforms have led to the recent resurgence
in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for …

Purpose This study investigated deep learning models for automatic segmentation to
support the development of daily online dose optimization strategies, eliminating the need …

Purpose The delineation of the clinical target volume (CTV) is a crucial, laborious and
subjective step in cervical cancer radiotherapy. The aim of this study was to propose and …

Purpose To develop a deep learning model that generates consistent, high-quality lymph
node clinical target volumes (CTV) contours for head and neck cancer (HNC) patients, as an …

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

Medical imaging techniques, such as (cone beam) computed tomography and magnetic
resonance imaging, have proven to be a valuable component for oral and maxillofacial …