Generative adversarial networks in digital pathology: a survey on trends and future potential ME Tschuchnig, GJ Oostingh, M Gadermayr Patterns 1 (6), 2020 | 104 | 2020 |
Anomaly detection in medical imaging-a mini review ME Tschuchnig, M Gadermayr Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 73 | 2022 |
Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential M Gadermayr, M Tschuchnig Computerized Medical Imaging and Graphics, 102337, 2024 | 27 | 2024 |
Sequential iot data augmentation using generative adversarial networks ME Tschuchnig, C Ferner, S Wegenkittl ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 16 | 2020 |
An asymmetric cycle-consistency loss for dealing with many-to-one mappings in image translation: a study on thigh MR scans M Gadermayr, M Tschuchnig, L Gupta, N Krämer, D Truhn, D Merhof, ... 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1182-1186, 2021 | 13 | 2021 |
Mixup-mil: Novel data augmentation for multiple instance learning and a study on thyroid cancer diagnosis M Gadermayr, L Koller, M Tschuchnig, LM Stangassinger, C Kreutzer, ... International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 9 | 2023 |
Evaluation of multi-scale multiple instance learning to improve thyroid cancer classification ME Tschuchnig, P Grubmüller, LM Stangassinger, C Kreutzer, ... 2022 Eleventh International Conference on Image Processing Theory, Tools and …, 2022 | 6 | 2022 |
Frozen-to-paraffin: Categorization of histological frozen sections by the aid of paraffin sections and generative adversarial networks M Gadermayr, M Tschuchnig, LM Stangassinger, C Kreutzer, ... Simulation and Synthesis in Medical Imaging: 6th International Workshop …, 2021 | 6 | 2021 |
Immutable and Democratic Data in Permissionless Peer-to-Peer Systems ME Tschuchnig, D Radovanovic, E Hirsch, AM Oberluggauer, G Schäfer 2019 Sixth International Conference on Software Defined Systems (SDS), 294-299, 2019 | 4 | 2019 |
Quantification of anomalies in rats’ spinal cords using autoencoders ME Tschuchnig, D Zillner, P Romanelli, D Hercher, P Heimel, GJ Oostingh, ... Computers in Biology and Medicine 138, 104939, 2021 | 3 | 2021 |
Improving automated thyroid cancer classification of frozen sections by the aid of virtual image translation and stain normalization M Gadermayr, M Tschuchnig, LM Stangassinger, C Kreutzer, ... Computer Methods and Programs in Biomedicine Update 3, 100092, 2023 | 1 | 2023 |
Multi-task Learning to Improve Semantic Segmentation of CBCT Scans using Image Reconstruction ME Tschuchnig, J Coste-Marin, P Steininger, M Gadermayr BVM Workshop, 243-248, 2024 | | 2024 |
Which Parameters Influence Success of Unconstrained Linear & Multilinear Interpolation for Data Augmentation in Multiple Instance Learning M Gadermayr, M Tschuchnig, L Stangassigner, C Erhardt-Kreutzer, ... 27th INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTINGAND COMPUTER …, 2024 | | 2024 |
MixUp-MIL: A Study on Linear & Multilinear Interpolation-Based Data Augmentation for Whole Slide Image Classification M Gadermayr, L Koller, M Tschuchnig, LM Stangassinger, C Kreutzer, ... arXiv preprint arXiv:2311.03052, 2023 | | 2023 |
A Commons-Compatible Implementation of the Sharing Economy: Blockchain-Based Open Source Mediation P Tschuchnig, M Mayr, M Tschuchnig, P Haber arXiv preprint arXiv:2303.07786, 2023 | | 2023 |
Inflation forecasting with attention based transformer neural networks M Tschuchnig, P Tschuchnig, C Ferner, M Gadermayr arXiv preprint arXiv:2303.15364, 2023 | | 2023 |
Correction to: Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks M Gadermayr, M Tschuchnig, LM Stangassinger, C Kreutzer, ... International Workshop on Simulation and Synthesis in Medical Imaging, C1-C1, 2021 | | 2021 |
Anomaly Detection in Medical Imaging-A Mini ME Tschuchnig, M Gadermayr arXiv preprint arXiv:2108.11986, 2021 | | 2021 |
Adversarial Networks—A Technology for Image Augmentation ME Tschuchnig Data Science–Analytics and Applications: Proceedings of the 2nd …, 2019 | | 2019 |
Quantification of Spinal Cord Anomalies using convolutional Autoencoders ME Tschuchnig, D Zillner, P Romanelli, D Hercher, P Heimel, GJ Oostingh, ... | | |