Address

Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Schöpfstraße 41, 6020 Innsbruck, Austria

Matthias Perkonigg

Postdoc

Medical University of Innsbruck

Biography

Matthias is a postdoctoral researcher at the EPICenter of the Medical University of Innsbruck. He has a background in computer science and medical image analysis. His research centres around advancements of machine learning methods with a focus on the specific requirements of medical data, particularly those of radiological and histo-pathological imaging.

He holds a MSc in Medical Informatics from the Technical University of Vienna and a PhD in Medical Imaging from the Medical University of Vienna. Before joining the Medical University of Innsbruck, he gained valuable industry experience working as a Machine Learning Engineer.

Selected publications

  • Hofmanninger, J.*, Perkonigg, M.*, Brink, J. A., Pianykh, O., Herold, C., & Langs, G. (2020). Dynamic memory to alleviate catastrophic forgetting in continuous learning settings. In International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI 2020 (pp. 359-368). Springer, Cham. * equal contribution
  • Perkonigg, M., Hofmanninger, J., Herold, C., Brink, J. A., Pianykh O., Prosch H., & Langs, G. (2021). Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging. Nature communications, 12, 5678.
  • Perkonigg, M., Hofmanninger, J., Herold, C., Prosch, H., & Langs, G. (2022). Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics. The Journal of Machine Learning for Biomedical Imaging (MELBA).
  • Fürböck, C., Perkonigg, M., Helbich, T., Pinker, K., Romeo, V., & Langs, G. (2022). Identifying phenotypic concepts discriminating molecular breast cancer sub-types. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 276-286). Cham: Springer Nature Switzerland.
  • Bastati, N., Perkonigg, M., Sobotka, D., Poetter-Lang, S., Fragner, R., Beer, A., Messner, A., Watzenboeck, M., Pochepnia, S., Kittinger, J., Herold, A., Kristic, A., Hodge, J.C., Traussnig, S., Trauner, M., Ba-Ssalamah, A. & Langs, G. (2023). Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study. European Radiology, 1-15.

  1. June 2022

    PhD in Medical Imaging

    Medical University of Vienna, Austria
  2. June 2018

    Dipl.-Ing. in Medical Informatics

    Technical University of Vienna, Austria
  3. November 2015

    BSc in Media Informatics and Visual Computing

    Technical University of Vienna, Austria

  1. since 2024
    Postdoctoral researcher
    Medical University of Innsbruck, Austria
  2. 2022-2024
    Senior Machine Learning Engineer
    contextflow, Vienna, Austria
  3. 2018-2022 Research Associate
    Research Associate
    Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria