Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1785 | 2018 |
Brats toolkit: translating brats brain tumor segmentation algorithms into clinical and scientific practice F Kofler, C Berger, D Waldmannstetter, J Lipkova, I Ezhov, G Tetteh, ... Frontiers in neuroscience 14, 501835, 2020 | 83 | 2020 |
Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence R McKinley, R Wepfer, L Grunder, F Aschwanden, T Fischer, C Friedli, ... NeuroImage: Clinical 25, 102104, 2020 | 65 | 2020 |
Confidence-based out-of-distribution detection: a comparative study and analysis C Berger, M Paschali, B Glocker, K Kamnitsas Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2021 | 46 | 2021 |
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient F Kofler, I Ezhov, F Isensee, F Balsiger, C Berger, M Koerner, B Demiray, ... arXiv preprint arXiv:2103.06205, 2021 | 37 | 2021 |
Modelhub. ai: Dissemination platform for deep learning models A Hosny, M Schwier, C Berger, EP Örnek, M Turan, PV Tran, L Weninger, ... arXiv preprint arXiv:1911.13218, 2019 | 21 | 2019 |