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

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 …

Background and purpose In this report, we describe our implementation and initial clinical
experience using 4D-MRI driven MR-guided online adaptive radiotherapy (MRgOART) for …

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

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 …

The hybrid MRI-radiotherapy machines, like the MR-linac (Elekta AB, Stockholm, Sweden)
installed at the UMC Utrecht (Utrecht, The Netherlands), will be able to provide real-time …

Introduction MR-guided adapted radiotherapy (MRgART) using a high field MR-linac has
recently become available. We report the estimated delivered fractional dose of the first five …

Monte Carlo (MC) simulation is commonly considered to be the most accurate dose
calculation method in radiotherapy. However, its efficiency still requires improvement for …

Recent developments in radiotherapy therapy demand high computation powers to solve
challenging problems in a timely fashion in a clinical environment. The graphics processing …

Background and purpose Monitoring the intrafraction motion and its impact on the planned
dose distribution is of crucial importance in radiotherapy. In this work we quantify the …