The liver tumor segmentation benchmark (lits) P Bilic, PF Christ, E Vorontsov, G Chlebus, H Chen, Q Dou, CW Fu, X Han, ... arXiv preprint arXiv:1901.04056, 2019 | 1152* | 2019 |
Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks. 2017 PF Christ, F Ettlinger, F Grün URL http://arxiv. org/abs/1702.05970. Cited on, 4, 0 | 439* | |
Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks PF Christ, F Ettlinger, F Grün, MEA Elshaera, J Lipkova, S Schlecht, ... arXiv preprint arXiv:1702.05970, 2017 | 430 | 2017 |
A taxonomy and library for visualizing learned features in convolutional neural networks F Grün, C Rupprecht, N Navab, F Tombari arXiv preprint arXiv:1606.07757, 2016 | 106 | 2016 |
A taxonomy and library for visualizing learned features in convolutional neural networks F Grün, C Rupprecht, N Navab, F Tombari 33rd International Conference on Machine Learning (ICML) Workshop on …, 2016 | 106 | 2016 |
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks PF Christ, F Ettlinger, G Kaissis, S Schlecht, F Ahmaddy, F Grün, ... 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 46 | 2017 |
Lits-liver tumor segmentation challenge P Christ, F Ettlinger, F Grün, J Lipkova, G Kaissis ISBI and MICCAI, 2017 | 25 | 2017 |
Towards Scenario-and Capability-Driven Dataset Development and Evaluation: An Approach in the Context of Mapless Automated Driving F Grün, M Nolte, M Maurer arXiv preprint arXiv:2404.19656, 2024 | | 2024 |