Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning

Martijn Starmans*

*Corresponding author for this work

Research output: Types of ThesisDoctoral ThesisInternal

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Abstract

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.
Original languageEnglish
Awarding Institution
  • Erasmus University Rotterdam
Supervisors/Advisors
  • Niessen, Wiro, Supervisor
  • Klein, Stefan, Co-supervisor
  • Visser, Jan-Jaap, Co-supervisor
Award date1 Feb 2022
Place of PublicationRotterdam
Print ISBNs978-94-6416-970-6
Publication statusPublished - 1 Feb 2022

Bibliographical note

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).

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