| Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential ME Tschuchnig, GJ Oostingh, M Gadermayr Patterns 1 (6), 2020 | 105 | 2020 |
| Generative adversarial networks for facilitating stain-independent supervised and unsupervised segmentation: a study on kidney histology M Gadermayr, L Gupta, V Appel, P Boor, BM Klinkhammer, D Merhof IEEE transactions on medical imaging 38 (10), 2293-2302, 2019 | 95 | 2019 |
| Anomaly detection in medical imaging-a mini review ME Tschuchnig, M Gadermayr Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 88 | 2022 |
| CNN cascades for segmenting sparse objects in gigapixel whole slide images M Gadermayr, AK Dombrowski, BM Klinkhammer, P Boor, D Merhof Computerized Medical Imaging and Graphics 71, 40-48, 2019 | 65 | 2019 |
| Which way round? A study on the performance of stain-translation for segmenting arbitrarily dyed histological images M Gadermayr, V Appel, BM Klinkhammer, P Boor, D Merhof Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 50 | 2018 |
| 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 | 44 | 2024 |
| Stain independent segmentation of whole slide images: A case study in renal histology L Gupta, BM Klinkhammer, P Boor, D Merhof, M Gadermayr 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 40 | 2018 |
| GAN-based image enrichment in digital pathology boosts segmentation accuracy L Gupta, BM Klinkhammer, P Boor, D Merhof, M Gadermayr Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 37 | 2019 |
| Evaluation of different distortion correction methods and interpolation techniques for an automated classification of celiac disease M Gadermayr, M Liedlgruber, A Uhl, A Vécsei Computer methods and programs in biomedicine 112 (3), 694-712, 2013 | 33 | 2013 |
| CNN cascades for segmenting whole slide images of the kidney M Gadermayr, AK Dombrowski, BM Klinkhammer, P Boor, D Merhof arXiv preprint arXiv:1708.00251, 2017 | 29 | 2017 |
| A comprehensive study on automated muscle segmentation for assessing fat infiltration in neuromuscular diseases M Gadermayr, C Disch, M Müller, D Merhof, B Gess Magnetic resonance imaging 48, 20-26, 2018 | 28 | 2018 |
| Segmenting renal whole slide images virtually without training data M Gadermayr, D Eschweiler, A Jeevanesan, BM Klinkhammer, P Boor, ... Computers in biology and medicine 90, 88-97, 2017 | 28 | 2017 |
| Shape curvature histogram: A shape feature for celiac disease diagnosis M Gadermayr, M Liedlgruber, A Uhl, A Vécsei Medical Computer Vision. Large Data in Medical Imaging: Third International …, 2014 | 27 | 2014 |
| Domain‐specific data augmentation for segmenting MR images of fatty infiltrated human thighs with neural networks M Gadermayr, K Li, M Müller, D Truhn, N Krämer, D Merhof, B Gess Journal of Magnetic Resonance Imaging 49 (6), 1676-1683, 2019 | 26 | 2019 |
| Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis M Gadermayr, H Kogler, M Karla, D Merhof, A Uhl, A Vécsei World journal of gastroenterology 22 (31), 7124, 2016 | 26 | 2016 |
| Unsupervisedly training GANs for segmenting digital pathology with automatically generated annotations M Gadermayr, L Gupta, BM Klinkhammer, P Boor, D Merhof arXiv preprint arXiv:1805.10059, 2018 | 23 | 2018 |
| Algorithms for microindentation measurement in automated Vickers hardness testing M Gadermayr, A Maier, A Uhl Tenth International Conference on Quality Control by Artificial Vision 8000 …, 2011 | 20 | 2011 |
| M cell maturation and cDC activation determine the onset of adaptive immune priming in the neonatal Peyer’s patch N Torow, R Li, TCA Hitch, C Mingels, S Al Bounny, N van Best, EL Stange, ... Immunity 56 (6), 1220-1238. e7, 2023 | 19 | 2023 |
| Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis M Gadermayr, G Wimmer, H Kogler, A Vécsei, D Merhof, A Uhl Computers in Biology and Medicine 102, 221-226, 2018 | 18 | 2018 |
| 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 | 14 | 2023 |
