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 …

Artificial Intelligence is providing astonishing results, with medicine being one of its favourite
playgrounds. Machine Learning and, in particular, Deep Neural Networks are behind this …

Purpose To develop an automated treatment planning strategy for external beam intensity‐
modulated radiation therapy (IMRT), including a deep learning‐based three‐dimensional …

With the advancement of treatment modalities in radiation therapy for cancer patients,
outcomes have improved, but at the cost of increased treatment plan complexity and …

The treatment planning process for patients with head and neck (H&N) cancer is regarded
as one of the most complicated due to large target volume, multiple prescription dose levels …

The goal of this study is to demonstrate the feasibility of a novel fully-convolutional
volumetric dose prediction neural network (DoseNet) and test its performance on a cohort of …

Purpose: To demonstrate knowledge‐based 3D dose prediction for external beam
radiotherapy. Methods: Using previously treated plans as training data, an artificial neural …

Recent works in automated radiotherapy treatment planning have used machine learning
based on historical treatment plans to infer the spatial dose distribution for a novel patient …

Purpose To develop a knowledge‐based automated planning pipeline that generates
treatment plans without feature engineering, using deep neural network architectures for …

Radiation therapy is a fundamental cancer treatment in the clinic. However, to satisfy the
clinical requirements, radiologists have to iteratively adjust the radiotherapy plan based on …