PhD Defence by Jakob Ambsdorf

From Promise to Utility of Medical Image Foundation Models: Methods, Evaluation, and Fetal Ultrasound Applications

  • Statens Naturhistoriske Museum
    Auditoriet (AUD)
    Sølvgade 83
    1307 København K
  • 14 September 2026, 13:00 – 16:00
  • Language: English
  • Host:
    Københavns Universitet

Assessment Committee

Professor Erik B Dam, DIKU, University of Copenhagen (Chairperson)
Professor Julia Schnabel, TUM
Professor and Dean of the Medical School Wiro Niessen, University of Groningen

Supervisors

Professor Mads Nielsen
Professor Aasa Feragen
Professor Martin Grønnebæk Tolsgaard

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Abstract

Medical image analysis faces two persistent bottlenecks: expert-labeled data are costly and scarce, while models often fail to generalize across scanners, populations, and acquisition settings. Foundation models promise to address both by learning reusable representations from large-scale unlabeled data. But how much of this promise is realized in clinically relevant settings?

This thesis introduces two domain-specific foundation models: AMAES for 3D brain MRI and UltraDINO for 2D fetal ultrasound. It first examines how pretraining methods from general computer vision transfer to specialized medical imaging domains.

It then demonstrates foundation model utility beyond benchmarks by evaluating UltraDINO for fetal aneuploidy detection, growth estimation, and spontaneous preterm birth prediction. Together, these studies examine when the promise holds in clinically motivated tasks, what adaptations are needed, and where limitations remain.