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Philipp Seeböck
Dipl. Ing. Philipp Seeböck, PhD

Department of Biomedical Imaging and Image-guided Therapy
Position: Research Associate (Postdoc)

T +43 1 40400 - 73922


Artificial Intelligence; Biomedical Research; Medical Informatics

Research group(s)

Research interests

  • Machine Learning
  • Deep Learning
  • Medical Image Analysis
  • Biomarker Detection
  • Representation Learning
  • Anomaly Detection

Selected publications

  1. Seeböck, P. et al. (2022) ‘Linking Function and Structure with ReSensNet’, Ophthalmology Retina, 6(6), pp. 501–511. Available at:
  2. Seeböck, Philipp, et al. "Exploiting epistemic uncertainty of anatomy segmentation for anomaly detection in retinal OCT." IEEE transactions on medical imaging 39.1 (2019): 87-98.
  3. Seeböck, Philipp, et al. "Unsupervised identification of disease marker candidates in retinal OCT imaging data." IEEE transactions on medical imaging 38.4 (2018): 1037-1047.
  4. Schlegl, T., Seeböck, P., Waldstein, S. M., Langs, G., & Schmidt-Erfurth, U. (2019). f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks. Medical image analysis.
  5. Hofer, D., Schmidt-Erfurth, U., Orlando, J. I., Goldbach, F., Gerendas, B. S., & Seeböck, P. (2022). Improving foveal avascular zone segmentation in fluorescein angiograms by leveraging manual vessel labels from public color fundus pictures. Biomedical Optics Express, 13(5), 2566-2580.