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Detail

Peter Kuess
Mag. Peter Kuess, PhD

Department of Radiotherapy
Position: Research Associate (Postdoc)

ORCID: 0000-0003-2961-1692
T +43 1 40400 21560
peter.kuess@meduniwien.ac.at

Keywords

Artificial Intelligence; Dose-Response Relationship, Radiation; Heavy Ion Radiotherapy; Image Processing, Computer-Assisted; Radiation Oncology; Radiation Protection; Radiotherapy

Research group(s)

Research interests

  • Proton and ion beam therapy
  • Adaptive radiotherapy 
  • Image-guided particle therapy
  • AI in radiotherapy

Techniques, methods & infrastructure

  • Dosimetry in proton and carbon ion beams
  • Medical image processing
  • Neural networks for radiotherapy
  • multi-parametric MRI

Selected publications

  1. Kuess, P. et al., 2017. Lateral response heterogeneity of Bragg peak ionization chambers for narrow-beam photon and proton dosimetry. Physics in Medicine & Biology, 62(24), pp.9189–9206. Available at: http://dx.doi.org/10.1088/1361-6560/aa955e.
  2. Khachonkham, S. et al., 2018. Characteristic of EBT-XD and EBT3 radiochromic film dosimetry for photon and proton beams. Physics in Medicine & Biology, 63(6), p.065007. Available at: http://dx.doi.org/10.1088/1361-6560/aab1ee.
  3. Kuess, P. et al., 2017. Association between pathology and texture features of multi parametric MRI of the prostate. Physics in Medicine & Biology, 62(19), pp.7833–7854. Available at: http://dx.doi.org/10.1088/1361-6560/aa884d.
  4. Georg, D. et al., 2014. Dosimetric Considerations to Determine the Optimal Technique for Localized Prostate Cancer Among External Photon, Proton, or Carbon-Ion Therapy and High-Dose-Rate or Low-Dose-Rate Brachytherapy. International Journal of Radiation Oncology*Biology*Physics, 88(3), pp.715–722. Available at: http://dx.doi.org/10.1016/j.ijrobp.2013.11.241.
  5. Kuess, P. et al., 2012. Using statistical measures for automated comparison of in-beam PET data. Medical Physics, 39(10), pp.5874–5881. Available at: http://dx.doi.org/10.1118/1.4749962.