Laszlo Papp
Center for Medical Physics and Biomedical Engineering
Position: PHD Student
ORCID: 0000-0002-9049-9989
T +43 1 40400 72350
laszlo.papp@meduniwien.ac.at
Keywords
Artificial Intelligence; Data Mining; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted
Research group(s)
- QIMP group
Head: Thomas Beyer, PhD, MBA
Research Area: Quantitative, combined imaging (PET/CT, PET/MR, SPECT/CT); Supporting clinical adoption of fully integrated PET/MRI; Image-based phenotyping and texture analysis
Members:
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
- Papp, L. et al., 2018. Optimized feature extraction for radiomics analysis of 18F-FDG-PET imaging. Journal of Nuclear Medicine, p.jnumed.118.217612. Available at: http://dx.doi.org/10.2967/jnumed.118.217612.
- 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: http://dx.doi.org/10.2967/jnumed.117.202267.
- Papp, L. et al., 2018. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis. Frontiers in Physics, 6. Available at: http://dx.doi.org/10.3389/fphy.2018.00051.