Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

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

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 …

Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …

Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to
computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal …

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of
radiation to tumors while sparing healthy tissues over multiple days. Computed tomography …

Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …

The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …

Objective Artificial intelligence (AI) has facilitated the analysis of medical imaging given
increased computational capacity and medical data availability in recent years. Although …

Artificial intelligence (AI) is expected to have a major effect on radiology as it demonstrated
remarkable progress in many clinical tasks, mostly regarding the detection, segmentation …