Detail

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:
  Lalith Kumar Shiyam Sundar
  Jacobo Cal-Gonzalez
  Ivo Rausch
  July Alejandra Gonzalez Valladares
  Alexander Berger
  Hunor Kertesz
  Denis Krajnc
  Thomas Beyer, PhD, MBA
  Laszlo Papp
  David Iommi

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, p.jnumed.118.217612. Available at: http://dx.doi.org/10.2967/jnumed.118.217612.
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: http://dx.doi.org/10.2967/jnumed.117.202267.
3. 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.