Dipl.-Ing. David Haberl
Department of Biomedical Imaging and Image-guided Therapy (Division of Nuclear Medicine)
Position: PHD Student
ORCID: 0000-0003-2050-097X
david.haberl@meduniwien.ac.at
Keywords
Artificial Intelligence; Biomedical Research; Molecular Imaging; Monte Carlo Method; Pattern Recognition, Automated; Positron-Emission Tomography
Research group(s)
- Christian Doppler Laboratory for Applied Metabolomics
Head:
Research Area: We investigate ways to better characterize tumors using non-invasive imaging techniques. This is important because tumours are constantly changing through mutations. In this way, an individual therapy should be possible and its success should be continuously monitored.
Members:
Research interests
Exploiting molecular imaging data to capture potential marker candidates for improved diagnosis and treatment stratification.
Techniques, methods & infrastructure
- Machine Learning
- Computer Vision
- Medical Image Analysis
- Monte Carlo Simulation (Geant4, GATE)
Selected publications
- Spielvogel, Haberl et al. (2024) ‘Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study’, The Lancet Digital Health, 6(4), pp. e251–e260. Available at: https://doi.org/10.1016/s2589-7500(23)00265-0.
- Haberl, D. et al. (2024) ‘Multicenter PET image harmonization using generative adversarial networks’, European Journal of Nuclear Medicine and Molecular Imaging. Available at: https://doi.org/10.1007/s00259-024-06708-8.