6. Dezember 2018
Kurzbeiträge von Prof. Dr. med. Schönberg (Direktor IKRN, UMM & Mitglied im M²OLIE Lenkungsausschuss) im White Paper/Sponsored Content von M²OLIE Partner Siemens Healthineers auf Seite 5 & Seite 8:
“Remake radiology into a quantitative discipline supported by statistical methods and artificial intelligence, promising a whole new level of individualized diagnostics. The goal is to develop large amounts of quantitative data from medical images using data-characterization algorithms — part of what Stefan Oswald Schönberg, managing director of the Institute for Clinical Radiology and Nuclear Medicine at University Hospital Mannheim, Germany, calls a “mathematical revolution in radiology.” In lay terms, there are big strides to be made in diagnostics by quantifying the results of visual images, including CT, PET, and
MRI scans. Quantifying images this way can help doctors reduce variations in diagnosis.”
“Radiomics. Radiomics refers to injecting quantitative discipline into radiology using statistical methods and artificial intelligence. Consider tumor clusters, which often share a high level of genetic heterogeneity with various tumor cell lines that can vary in their aggressiveness and their response to treatment. Their composition can be a decisive factor in the success of treatment. Radiomics, observes Stefan Oswald Schönberg, can give doctors a precise image of these clusters through quantitative analyses of imaging information, along with artificial intelligence-based interpretations of clinical, genetic, and imaging data. This allows doctors to tailor treatment more precisely to individual patients.”
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