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Maximilian Tschuchnig

Titel/Grad: DI, BSc

Funktion: Junior Researcher

  • Softwareentwicklung
  • Softwareengineering
  • Machine Learning
  • Deep Learning

M. Gadermayr, M. E. Tschuchnig, L. Gupta, N. Krämer, D. Truhn, D. Merhof, and B. Gess, “An asymmetric cycle-consistency loss for dealing with many-to-one mappings in image translation: a study on thigh mr scans,” in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1182–1186

M. Gadermayr, M. E. Tschuchnig, L. M. Stangassinger, C. Kreutzer, S. Couillard-Despres, G. J. Oostingh, and A. Hittmair, “Frozen-to-paraffin: Categorization of histological frozen sections by the aid of paraffin sections and generative adversarial networks,” in International Workshop on Simulation and Synthesis in Medical Imaging, 2021, pp. 99–109.

M. E. Tschuchnig, D. Zillner, P. Romanelli, D. Hercher, P. Heimel, G. J. Oostingh, S. Couillard-Després, and M. Gadermayr, “Quantification of anomalies in rats’ spinal cords using autoencoders,” Computers in Biology and Medicine, vol. 138, p. 104939, 2021.

M. E. Tschuchnig and M. Gadermayr, “Anomaly detection in medical imaging-a mini review,” Data Science–Analytics and Applications, pp. 33–38, 2022.

M. E. Tschuchnig, P. Grubmüller, L. M. Stangassinger, C. Kreutzer, S. Couillard-Després, G. J. Oostingh, A. Hittmair, and M. Gadermayr, “Evaluation of multiscale multiple instance learning to improve thyroid cancer classification,” in 2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 2022, pp. 1–6.



fon:  +43 (0)50-2211-1335
fax: +43 (0)50-2211-1349
mobil: +43 (0) 699 11320170
email: maximilian.tschuchnig@fh-salzburg.ac.at

Maximilian Tschuchnig

Maximilian Tschuchnig (Foto: FH Salzburg)