Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …

Tissue mimicking materials (TMMs), typically contained within phantoms, have been used
for many decades in both imaging and therapeutic applications. This review investigates the …

Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in
combination with other methods. The planning and delivery of radiotherapy treatment is a …

Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …

Radiation therapy (RT) continues to be one of the mainstays of cancer treatment.
Considerable efforts have been recently devoted to integrating MRI into clinical RT planning …

To enable magnetic resonance (MR)-only radiotherapy and facilitate modelling of radiation
attenuation in humans, synthetic CT (sCT) images need to be generated. Considering the …

MRI and CT are most widely used medical imaging modalities. It is often necessary to
acquire multi-modality images for diagnosis and treatment such as radiotherapy planning …

Abstract Magnetic Resonance Imaging (MRI) guided Radiation Therapy is a hot topic in the
current studies of radiotherapy planning, which requires using MRI to generate synthetic …

The use of dedicated magnetic resonance simulation (MR‐SIM) platforms in Radiation
Oncology has expanded rapidly, introducing new equipment and functionality with the …