Following on from the 2015 Lancet Oncology Commission on expanding global access to
radiotherapy, Radiotherapy and theranostics: a Lancet Oncology Commission was created …

Radiomics is a high-throughput approach to image phenotyping. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …

An important need exists for strategies to perform rigorous objective clinical-task-based
evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need …

Background Myocardial perfusion (MP) SPECT is a well-established method for diagnosing
cardiac disease, yet its radiation risk poses safety concern. This study aims to apply and …

Artificial intelligence (AI)-based methods for medical imaging, and more specifically PET,
hold exciting promise in multiple stages of the imaging–technology–development lifecycle …

Background Artificial intelligence‐based methods have generated substantial interest in
nuclear medicine. An area of significant interest has been the use of deep‐learning (DL) …

Background The advancement of x‐ray CT into the domains of photon counting spectral
imaging and dynamic cardiac and perfusion imaging has created many new challenges and …

Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with
several RPTs already well established in the treatment of several different types of cancers …

Schematic of supervised, unsupervised, and semisupervised machine learning (left) and
reinforcement learning (right). Common algorithms used in supervised and unsupervised …

There is increasing interest in clinical trials that use technologies and other innovative
operational approaches to organise trial activities around trial participants instead of …