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Matthias Perkonigg
Matthias Perkonigg
Verified email at meduniwien.ac.at
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Year
CHAOS challenge-combined (CT-MR) healthy abdominal organ segmentation
AE Kavur, NS Gezer, M Barış, S Aslan, PH Conze, V Groza, DD Pham, ...
Medical Image Analysis 69, 101950, 2021
1372021
Dynamic memory to alleviate catastrophic forgetting in continuous learning settings
J Hofmanninger, M Perkonigg, JA Brink, O Pianykh, C Herold, G Langs
International Conference on Medical Image Computing and Computer-Assisted …, 2020
132020
Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging
M Perkonigg, J Hofmanninger, CJ Herold, JA Brink, O Pianykh, H Prosch, ...
Nature Communications 12 (1), 1-12, 2021
92021
Continual active learning for efficient adaptation of machine learning models to changing image acquisition
M Perkonigg, J Hofmanninger, G Langs
International Conference on Information Processing in Medical Imaging, 649-660, 2021
42021
Asymmetric cascade networks for focal Bone lesion prediction in multiple myeloma
R Licandro, J Hofmanninger, M Perkonigg, S Röhrich, MA Weber, ...
arXiv preprint arXiv:1907.13539, 2019
42019
Unsupervised deep clustering for predictive texture pattern discovery in medical images
M Perkonigg, D Sobotka, A Ba-Ssalamah, G Langs
arXiv preprint arXiv:2002.03721, 2020
32020
Machine learning in radiology: terminology from individual timepoint to trajectory
G Langs, U Attenberger, R Licandro, J Hofmanninger, M Perkonigg, ...
Der Radiologe 60 (1), 6-14, 2020
22020
Maschinelles Lernen in der Radiologie
G Langs, U Attenberger, R Licandro, J Hofmanninger, M Perkonigg, ...
Der Radiologe 60 (1), 6-14, 2020
22020
Detecting bone lesions in multiple myeloma patients using transfer learning
M Perkonigg, J Hofmanninger, B Menze, MA Weber, G Langs
Data Driven Treatment Response Assessment and Preterm, Perinatal, and …, 2018
22018
Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics
M Perkonigg, J Hofmanninger, C Herold, H Prosch, G Langs
arXiv preprint arXiv:2111.13069, 2021
2021
Pseudo-domains in imaging data improve prediction of future disease status in multi-center studies
M Perkonigg, P Mesenbrink, A Goehler, M Martic, A Ba-Ssalamah, ...
arXiv preprint arXiv:2111.07634, 2021
2021
Maschinelles Lernen in der Radiologie: Begriffsbestimmung vom Einzelzeitpunkt bis zur Trajektorie.
G Langs, U Attenberger, R Licandro, J Hofmanninger, M Perkonigg, ...
Der Radiologe 60 (1), 2020
2020
Convolutional neural networks for bone lesion detection in medical imaging data
M Perkonigg
Wien, 2018
2018
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