Zum Hauptinhalt springen

Michael Gadermayr

Titel/Grad: FH-Prof. Dr.

Funktion: Senior Lecturer

Kompetenzbereiche:
  • Machine Learning
  • Deep Learning
  • Medical and Biological Image Analysis
Lehrveranstaltungen:
  • Mathematik
  • Statistik
  • Deep Learning
  • Medieninformatik
  • Medien-Technologie
Ausgewählte Publikationen:

Gadermayr, M., Heckmann, L., Li, K., Bähr, F., Müller, M., Truhn, D., ... & Gess, B. (2021). Image-to-Image Translation for Simplified MRI Muscle Segmentation. Frontiers in Radiology, 1, 3.

Tschuchnig, M. E., Zillner, D., Romanelli, P., Hercher, D., Heimel, P., Oostingh, G. J., ... & Gadermayr, M. (2021). Quantification of anomalies in rats’ spinal cords using autoencoders. Computers in Biology and Medicine, 104939.

Michael Gadermayr,  Lotte Heckmann, Kexin Li, Friederike Bähr, Madlaine Müller, Daniel Truhn, Dorit Merhof, Burkhard Gess, Image-to-Image Translation for Simplified MRI Muscle Segmentation, Frontiers in Radiology, 2021

Maximilian E. Tschuchnig, Gertie J. Oostingh and Michael Gadermayr, Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential, CellPress Pattern, 2020

Laxmi Gupta, Barbara M. Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr, GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019

Michael Gadermayr, Laxmi Gupta, Vitus Appel, Peter Boor, Barbara M. Klinkhammer, Dorit Merhof, Generative Adversarial Networks for Facilitating Stain-Independent Supervised & Unsupervised Segmentation: A Study on Kidney Histology, IEEE Transaction on Medical Imaging (TMI), 2019

Michael Gadermayr, Vitus Appel, Barbara M. Klinkhammer, Peter Boor and Dorit Merhof, Which Way Round? A Study on the Performance of Stain-Translation for Segmenting Arbitrarily Dyed Histological Images, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018

Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr, Stain Independent Segmentation of Whole Slide Images: A Case Study in Renal Histology, IEEE International Symposium on Biomedical Imaging (ISBI), 2018

Michael Gadermayr, Georg Wimmer, Hubert Kogler, Andreas Vécsei, Dorit Merhof and Andreas Uhl, Automated Classification of Celiac Disease During Upper Endoscopy: Status Quo and Quo Vadis, Computers in Biology and Medicine, 2018

Michael Gadermayr, Kexin Li, Madlaine Müller, Daniel Truhn, Nils Krämer, Dorit Merhof, Domain Specific Data Augmentation for Segmenting MR Images of Fatty Infiltrated Human Thighs with Neural Networks, Journal of Magnetic Resonance Imaging, 2018

Michael Gadermayr, Constantin Disch, Madlaine Müller, Dorit Merhof and Burkhard Gess, A Comprehensive Study on Automated Muscle Segmentation for Assessing Fat Infiltration in Neuromuscular Diseases, Magnetic Reconance Imaging, 2018

M. Gadermayr, L. Heckmann, K. Li, F. Bähr, M. Müller, D. Truhn, D. Merhof, and B. Gess, “Image-to-image translation for simplified mri muscle segmentation,” Frontiers in Radiology, p. 3, 2021.

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

F. Bähr, B. Gess, M. Müller, S. Romanzetti, M. Gadermayr, C. Kuhl, S. Nebelung, J. B. Schulz, and M. F. Dohrn, “Semi-automatic mri muscle volumetry to diagnose and monitor hereditary and acquired polyneuropathies,” Brain sciences, vol. 11, no. 2, p. 202, 2021.

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. Uray, E. Hirsch, G. Katzinger, and M. Gadermayr, “Beyond desktop computation: Challenges in scaling a gpu infrastructure,” in Data Science–Analytics and Applications, 2022, pp. 75–81.

M. Siller, L. M. Stangassinger, C. Kreutzer, P. Boor, R. D. Bulow, T. J. Kraus, S. Von Stillfried, S. Wolfl, S. Couillard-Despres, G. J. Oostingh, Anton Hittmair, Michael Gadermayr, “On the acceptance of “fake” histopathology: A study on frozen sections optimized with deep learning,” Journal of Pathology Informatics, vol. 13, 2022.

F. Duong, M. Gadermayr, D. Merhof, C. Kuhl, P. Bruners, S. H. Loosen, C. Roderburg, D. Truhn, and M. F. Schulze-Hagen, “Automated major psoas muscle volumetry in computed tomography using machine learning algorithms,” International Journal of Computer Assisted Radiology and Surgery, vol. 17, no. 2, pp. 355–361, 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.

L. Gupta, B. M. Klinkhammer, C. Seikrit, N. Fan, N. Bouteldja, P. Gräbel, M. Gadermayr, P. Boor, and D. Merhof, “Large-scale extraction of interpretable features provides new insights into kidney histopathology–a proof-of-concept study,” Journal of Pathology Informatics, p. 100097, 2022.

 

Liste aller Publikationen: https://scholar.google.com/citations?user=QGSF79AAAAAJ&hl=en

Projekte:
Kontaktdaten:

fon: +43 (0)50-2211-1341
fax: +43 (0)50-2211-1349
email: michael.gadermayr@fh-salzburg.ac.at

 

Michael Gadermayr

Michael Gadermayr (Foto: FH Salzburg)