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* Correspondence: Nuclear Medicine and Diagnostic Imaging Section, International Atomic Energy Agency, Vienna, Austria Full list of author information is available at the end of the article Medical imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and single-photon emission computed tomography (SPECT) have acquired a central role in the clinical management of a wide variety of diseases. The unique advantage of imaging is the non-invasive characterisation and quantification of the presence of pathophysiological processes at different stages of diseases and the ability to monitor the disease. The advent of hybrid imaging PET/CT, SPECT/CT and PET/MRI brought the best of two worlds for the patient’s benefit, but it represents a continuous challenge in standardising and optimising methodologies for the health professionals responsible for imaging. In this setting, we are pleased to announce the publication of two distinct thematic series, one dedicated to artificial intelligence (AI) and the second specifically dedicated to technologists. Optimal use of hybrid and multimodality medical imaging data can maybe further improved by applying artificial intelligence, to speed-up and increase the diagnostic accuracy in various diseases and prediction of response on therapy. The term AI is applied when a device mimics cognitive functions, such as learning and problem solving. More generally, AI refers to a field of computer science dedicated to the creation of systems performing tasks that usually require human intelligence, branching off into different techniques. Machine learning, deep learning and artificial neural networks are those approaches that allow computers to learn from data and have emerged as promising in the fields of nuclear medicine and in radiology. The majority of the physicians are not experienced in AI applications, due to a gap in knowledge and lack of training facilities or some amongst us with disbelieve in or even fear AI. We however cannot ignore the development of AI systems in medical imaging, as is visible in the exploding number of publications and abstracts on medical imaging congresses, particularly in the field of radiology. Nuclear medicine is growing less rapidly in AI applications, probably due to a less amount of acquired data, but is rising as well, as the number acquisition procedures, in particular PET/CT, are growing. So, should we see AI as an opportunity or as a threat in our profession? AI is believed to be a tremendous opportunity for its improvement. Similar to our natural intelligence, AI algorithms look at medical images to identify patterns after being trained using vast numbers of examinations and images. In this scenario, AI is not a threat to our imaging profession. With the irreversible increase in imaging data and the possibility to identify findings that

Two new thematic series—spotlight on artificial intelligence and a specific platform for technologist