MRI can help to categorize tissues as malignant or non-malignant both anatomically and
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …

The treatment of cancer with proton radiation therapy was first suggested in 1946 followed
by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated …

The integration of magnetic resonance imaging (MRI) for guidance in external beam
radiotherapy has faced significant research and development efforts in recent years. The …

Adaptive radiotherapy emerged over 20 years ago and is now an established clinical
practice in a number of organ sites. No one solution for adaptive therapy exists. Rather …

Magnetic resonance‐guided radiation therapy (MRgRT) is a promising approach to
improving clinical outcomes for patients treated with radiation therapy. The roles of image …

Purpose The first aim of this work is to present a novel deep convolution neural network
(DCNN) multiplane approach and compare it to single-plane prediction of synthetic …

We present DeepDose, a deep learning framework for fast dose calculations in radiation
therapy. Given a patient anatomy and linear-accelerator IMRT multi-leaf-collimator shape or …

Quantitative radiomics features, extracted from medical images, characterize tumour-
phenotypes and have been shown to provide prognostic value in predicting clinical …

Background Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear
accelerators (MR‐Linacs) can administer a tailored radiation dose at each treatment fraction …

Advances in radiotherapy technologies have enabled more precise target guidance,
improved treatment verification, and greater control and versatility in radiation delivery …