Zusammenfassung
Many imaging biomarkers (IBs) fail clinical translation. The main reason is not a lack of utility, but translational gaps [1] during validation and qualification. One important problem in this context is the landscape of existing IT systems in the clinical environment. Systems are highly heterogeneous and proprietary, causing significant translational challenges that are often purely infrastructural in nature.
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O’Connor JPB, Aboagye EO, Adams JE, et al. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol. 2017;14(3):169–186.
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Petersen, J. et al. (2018). Abstract: Leveraging Open Source Software to Close Translational Gaps in Medical Image Computing. In: Maier, A., Deserno, T., Handels, H., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2018. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-56537-7_18
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DOI: https://doi.org/10.1007/978-3-662-56537-7_18
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