| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1168 | 2023 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019 | 1022 | 2019 |
| The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature communications 13 (1), 4128, 2022 | 874 | 2022 |
| Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields PF Christ, MEA Elshaer, F Ettlinger, S Tatavarty, M Bickel, P Bilic, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 823 | 2016 |
| 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 | 431 | 2017 |
| Automated Whole‐Body Bone Lesion Detection for Multiple Myeloma on 68Ga‐Pentixafor PET/CT Imaging Using Deep Learning Methods L Xu, G Tetteh, J Lipkova, Y Zhao, H Li, P Christ, M Piraud, A Buck, K Shi, ... Contrast media & molecular imaging 2018 (1), 2391925, 2018 | 153 | 2018 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms. arXiv 2019 AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019 | 89 | 2019 |
| The liver tumor segmentation benchmark (lits). arXiv 2019 P Bilic, PF Christ, E Vorontsov, G Chlebus, H Chen, Q Dou, CW Fu, X Han, ... arXiv preprint arXiv:1901.04056 15, 16, 2019 | 47 | 2019 |
| 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, ... IEEE International Symposium on Biomedical Imaging 2017, 2017 | 46 | 2017 |
| Diabetes60 - Inferring Bread Units From Food Images Using Fully Convolutional Neural Networks P F. Christ, S Schlecht, F Ettlinger, F Grun, C Heinle, S Tatavatry, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 28* | 2017 |
| Lits-liver tumor segmentation challenge P Christ, F Ettlinger, F Grün, J Lipkova, G Kaissis ISBI and MICCAI, 2017 | 25 | 2017 |
| MedShapeNet--A large-scale dataset of 3D medical shapes for computer vision J Li, Z Zhou, J Yang, A Pepe, C Gsaxner, G Luijten, C Qu, T Zhang, ... arXiv preprint arXiv:2308.16139, 2023 | 17 | 2023 |
| Human-drone-interaction: A case study to investigate the relation between autonomy and user experience PF Christ, F Lachner, A Hösl, B Menze, K Diepold, A Butz Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 13 | 2016 |
| W-Net for Whole-Body Bone Lesion Detection on Ga-Pentixafor PET/CT Imaging of Multiple Myeloma Patients L Xu, G Tetteh, M Mustafa, J Lipkova, Y Zhao, M Bieth, P Christ, M Piraud, ... International Workshop on Reconstruction and Analysis of Moving Body Organs …, 2017 | 9 | 2017 |
| Automated unsupervised segmentation of liver lesions in ct scans via cahn-hilliard phase separation J Lipková, M Rempfler, P Christ, J Lowengrub, BH Menze arXiv preprint arXiv:1704.02348, 2017 | 8 | 2017 |
| October. Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields PF Christ, MEA Elshaer, F Ettlinger, S Tatavarty, M Bickel, P Bilic, ... International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 7 | 2016 |
| Convolutional Neural Networks for Classification and Segmentation of Medical Images PF Christ Technische Universität München, 2017 | 1 | 2017 |
| Die Hauptkomponentenanalyse von ADC-Histogrammen als prädiktiver Faktor im HCC G Kaissis, F Ettlinger, F Ahmaddy, P Chakrabarti, P Christ, B Menze, ... RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden …, 2017 | | 2017 |
| Predicting patient survival in hepatocellular carcinoma (HCC) from diffusion weighted magnetic resonance imaging (DW-MRI) data using neural networks F Ettlinger, P Christ, G Kaissis, F Ahmaddy, F Grün, S Schlecht, ... Proc. Intl. Soc. Mag. Reson. Med 25, 2017, 1785 | | 1785 |
Bjoern H MenzeUniversität ZürichVerified email at uzh.ch
