Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …

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 …

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

Purpose Although large datasets are available, to learn a robust dose prediction model from
a limited dataset still remains challenging. This work employed cascaded deep learning …

Background and purpose Tools for auto-segmentation in radiotherapy are widely available,
but guidelines for clinical implementation are missing. The goal was to develop a workflow …

Accurate segmentation of multiple organs in the head, neck, chest, and abdomen from
medical images is an essential step in computer-aided diagnosis, surgical navigation, and …

Purpose This study aimed to use deep learning–based dose prediction to assess head and
neck (HN) plan quality and identify suboptimal plans. Methods and Materials A total of 245 …

Radiation therapy (RT) is currently the main clinical treatment of tumors. Before treatment
initiation, precise delineation of the planned target volume (PTV) and organs at risk (OAR) is …

Background Deep learning‐based auto‐planning is an active research field; however, for
some tasks a treatment planning system (TPS) is still required. Purpose To introduce a deep …

Deep learning has been utilized in knowledge-based radiotherapy planning in which a
system trained with a set of clinically approved plans is employed to infer a three …