State-of-the-art imaging technology processes and the large-scale, novel, computational analysis of data sets, including the use of machine learning and artificial intelligence, are improving our understanding of human health function and disease. This, in turn, is creating a powerful driver to achieve precision medicine through quantitative imaging informatics. Computational quantitative analysis of medical images provides opportunities in aiding diagnosis, deriving diagnostic imaging biomarkers, providing prognostic biomarkers, aiding surgical decision-making and therapy planning, while offering clinicians with early indications of response to therapy.

The current advances in high-throughput identification, extraction, and analysis of quantitative MR-based functional imaging features, in the context of radiomics, for the diagnostic and prognostic characterization of paediatric brain tumours are the focus of this seminar’s presentation by Professor Theo Arvanitis.

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