Radiomics uses quantitative medical imaging features and AI to create predictive models which can be used as biomarkers. In this thesis, we have developped an adaptive radiomics framework to automatically optimize the radiomics workflow per application and demonstrate its use to create biomarkers in eight different clinical applications.

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W.J. Niessen (Wiro)
Erasmus University Rotterdam
This work is part of the research programme STRaTeGy with project numbers 14929, 14930, and 14932, which is (partly) financed by the Dutch Research Council (NWO).
ASCI dissertation series
Department of Radiology

Starmans, M.P.A. (2022, February). Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning (No. 431). ASCI dissertation series. Erasmus University Rotterdam. Retrieved from