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Marko Grahovac, MSc

Department of Biomedical Imaging and Image-guided Therapy (Division of Nuclear Medicine)
Position: PHD Student

ORCID: 0000-0002-3323-778X
T +43 1 40400-55850


Artificial Intelligence; Data Mining; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted

Research group(s)

Research interests

Machine learning, image processing, personalized medicine, tumour characterization

Techniques, methods & infrastructure

Techniques, Methods: In vivo feature engineering, Radiomics, Feature selection, Ensemble learning, Monte Carlo cross-validation

Infrastructure: high-performance computing (ITSC), Microsoft Azure cloud computing

Selected publications

  1. Papp, L. et al., 2018. Optimized Feature Extraction for Radiomics Analysis of 18F-FDG PET Imaging. Journal of Nuclear Medicine, 60(6), pp.864–872. Available at:
  2. Papp, L. et al., 2017. Glioma Survival Prediction with Combined Analysis of In Vivo11C-MET PET Features, Ex Vivo Features, and Patient Features by Supervised Machine Learning. Journal of Nuclear Medicine, 59(6), pp.892–899. Available at:
  3. Papp, L. et al., 2018. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis. Frontiers in Physics, 6. Available at:
  4. Grubmüller, B. et al., 2018. PSMA Ligand PET/MRI for Primary Prostate Cancer: Staging Performance and Clinical Impact. Clinical Cancer Research, 24(24), pp.6300–6307. Available at:
  5. Papp, L. et al., 2019. Comparison of machine learning-driven lesion classifiers in prostate PET/MRI cases over different repeatability categories of radiomic features. 57. Jahrestagung der Deutschen Gesellschaft für Nuklearmedizin. Available at: