The AI Imaging Hub team are a highly experienced team of dedicated clinical and research scientists offering an extensive collection of knowledge, skills and experience to oncology imaging. The Hub is led by Professor Dow-Mu Koh and Dr Christina Messiou. Image Prof Koh, Co-Director of the AI Imaging Hub Prof Koh is Consultant Radiologist in Functional Imaging at The Royal Marsden Hospital and Professor in Functional Cancer Imaging at The Institute of Cancer Research, London. Prof Koh’s has a particular interest interest in body diffusion-weighted (DW) magnetic resonance imaging (MRI) and whole-body MRI. Recent research includes body MR fingerprinting, radiomics and using artificial intelligence and machine learning to improve imaging diagnostics and workflows. He was the Director of the National Institute of Health Research (NIHR) Clinical Research Facility at The Royal Marsden Hospital and The Institute of Cancer Research. Prof Koh is a Fellow and Chair of the Executive Board of the International Cancer Imaging Society, Fellow of European Society of Gastrointestinal and Abdominal Radiology, Senior Fellow of International Society of Magnetic Resonance in Medicine and was awarded the Gold Medal of the International Cancer Imaging Society (2018). He was an associate editor for Radiology (2011-2018). He was awarded the Barclay Medal in 2013 for his contributions to the British Journal of Radiology and has more than 250 publications in peer reviewed journals and textbooks. View a selection of peer-review publications by Prof Koh Dr Messiou, Co-Director of the AI Imaging Hub In 2011, Dr Messiou became a Consultant Radiologist at The Royal Marsden and is a core member of multidisciplinary teams for sarcoma, melanoma and haemato-oncology. She is a member of the European Organisation for Research and Treatment of Cancer (EORTC) Imaging group and in 2012 was appointed chair of the imaging subcommittee for the EORTC Soft Tissue and Bone Sarcoma Group. In 2014 she was appointed Roentgen Professor by the Royal College of Radiologists and is an elected Fellow of the International Cancer Imaging Society. In 2019 she was awarded the Royal College of Radiologists and NIHR Clinical Research Network Outstanding Clinical Radiology Researcher Award. She has published more than 130 peer reviewed publications and is a Team leader and Honorary Faculty at The Institute of Cancer Research (ICR). Following on from her early research she was one of the first radiologists to provide a comprehensive whole-body MRI service for patients with myeloma and is established internationally as an authority. Dr Messiou is Digital Theme Lead at the NIHR Biomedical Research Centre at The Royal Marsden and ICR and co-director of the AI Imaging hub at The Royal Marsden. She is committed to using her experience as a clinical radiologist, researcher and educator for the benefit of patients with cancer. View a selection of peer-review publications by Dr Messiou Ana Riberio, AI Transformation Lead Ana Riberio completed her degree in Nuclear Medicine (BSc (Hons)) at the ESS Porto in Portugal, followed by a PgDip and MRes at City University of London and is currently undertaking a PhD at Erasmus MC. She previously worked as a senior nuclear medicine research technologist at The Royal Marsden Clinical Research Facility. Following on from her clinical work, Ana held a position as Research Project Manager for an NIHR Invention for Innovation (i4i) funded project and is currently AI Transformation Lead for the AI Imaging Hub. Her previous research addressed patients’ awareness and perception of radiation exposure during bone and PET/CT scanning. Her work was presented at the British Nuclear Medicine Society (BNMS) conference in April 2019 and received first prize under the Radiographers, Technologists and Nurses category. This has also led to a number of articles, and presentations at international conferences. She has also contributed to other imaging research studies in the fields of Nuclear Medicine and Radiology. Ana’s current research is looking at understanding patients and healthcare professionals’ views on independent patient access to their imaging records – how access to a digital platform could better support and engage patients to become active users of digital health services – which is in line with changes to current patient record systems across the UK and internationally. As Transformation lead at the AI Imaging Hub, together with the two directors, she oversees a diverse team and skill mix as well the Hub research portfolio and provides regulatory and governance management to the Hub data driven projects, particularly in the field of imaging and artificial intelligence. Dr Matthew Orton, Radiomics and Machine Learning Lead Dr Matthew Orton was appointed as the Radiomics and Machine Learning Lead within the AI hub in early 2021, having worked as a Staff Scientist in the Division of Radiotherapy and Imaging at The Institute of Cancer Research (ICR) for the previous 15 years. With a background in Bayesian Signal Processing, he has made important developments in the application of statistical modelling techniques to functional MR image modelling, and in his new role is bringing the same rigour to bear in the world of radiomics. His current focus is on developing radiomics methods that lead to interpretable models, which is a crucial and under-developed step in translating radiomics signatures discovered in early-phase trials through to clinical deployment and improved outcomes for patients. Dr Orton's team Dr Evan Hann joined the AI hub in the spring of 2021 as a Machine Learning for Radiology Analyst having recently gained a DPhil for research in deep ensemble learning and cardiovascular medical image analysis at the University of Oxford. He is currently researching mathematical and deep-learning techniques to capture 3D tumour shape information from radiological data to augment the radiomics feature sets typically studied. Dr Helen Wang also joined the AI hub in mid 2021 as a Machine Learning for Radiology Analyst, having recently gained a PhD from the University of Surrey for research in the reproducibility and repeatability of radiomics in CT images and applications in Non-small Cell Lung Cancer using classic machine learning techniques. Her current research focus is on image and data harmonization techniques to enable radiomics signatures to be discovered in large heterogeneous multi-centre data sets. Dr Nickolas Papanikolaou, Machine Learning Imaging Lead Dr Nickolas Papanikolaou is the Machine Learning Imaging Lead at The Royal Marsden and Principal Investigator in Oncologic Imaging at CHAMPALIMAUD FOUNDATION as well as the research group leader of the Computational Clinical Imaging Group. He is an Affiliated Researcher at Karolinska Institute and a Senior Affiliated Researcher at the Institute of Computer Science – FORTH. Dr. Nikolaos Papanikolaou studied biomedical engineering while he obtained his Ph.D. from the Medical School of the University of Crete. He has been a research associate of the Department of Radiology, University Hospital of Heraklion, from 1999 to 2009. He has published 99 scientific papers in peer-reviewed international journals and 20 chapters in international books. At the same time, he edited a series of 3 books on Diffusion-Weighted Imaging Applications in GI, GU, and Hepatobiliary systems. He has delivered more than 120 invited lectures in international congresses and educational courses. He served as a member of the editorial board of European Radiology in the section of experimental radiology while he was a member of the abdominal subcommittee of ECR. He has been awarded two research scholarships from ECR. He is an honorary member of the Spanish Society of Gastrointestinal Radiology (SEDIA). The main focus of his research is the development and validation of radiomics signatures for cancer applications. He recently initiated the development of a Radiomics Network comprising luminary clinical sites in the US and Europe to advance research in that area of Radiomics. He is the section editor on AI, Radiomics, and Machine Learning in Cancer Imaging, while he is currently the scientific manager of a pan-European project that focuses on AI and ML applications in prostate cancer (Pro-Cancer-I).