Imaging grand round

Grand round
Chairs: C. Brightling (Leicester (Leicestershire), United Kingdom), T. Blum (Berlin, Germany)
Aims: To describe the latest advances in imaging technology with a focus on diagnosis of early disease and prevention; to evaluate the role of artificial intelligence in imaging and the integration of artificial intelligence with emerging imaging techniques, such as magnetic resonance imaging (MRI) and quantitative computed tomography (CT), as well as deep learning; to evaluate the use of radiogenomics in classifying patients who will benefit from cancer treatment and predict outcomes using texture analysis; and to describe the results of imaging twin studies in estimating the role of genetic, epigenetic and environmental effects on respiratory diseases.

Deep learning and its applications to lung imaging M. Vakalopoulou (Gif-sur-Yvette, France)
Artificial intelligence  in lung cancer: where are we now? F. Gleeson (Oxford (Oxfordshire), United Kingdom)
The future is here in thoracic oncologic imaging: role of radiogenomics Z. Bodalal Elkarghali (Netherlands)
Imaging twin studies to unravel the genetic, epigenetic and environmental background of lung diseases: Part I Á. Tárnoki (Budapest, Hungary)
Imaging twin studies to unravel the genetic, epigenetic and environmental background of lung diseases: Part II D. Tarnoki (Budapest, Hungary)