| 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 | 2067 | 2018 |
| 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 | 1271 | 2023 |
| 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 | 840 | 2016 |
| Self-organization and symmetry breaking in intestinal organoid development D Serra, U Mayr, A Boni, I Lukonin, M Rempfler, L Challet Meylan, ... Nature 569 (7754), 66-72, 2019 | 500 | 2019 |
| Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections R Cai, C Pan, A Ghasemigharagoz, MI Todorov, B Förstera, S Zhao, ... Nature neuroscience 22 (2), 317-327, 2019 | 450 | 2019 |
| 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 | 441 | 2017 |
| VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... Medical image analysis 73, 102166, 2021 | 262 | 2021 |
| Identifying the best machine learning algorithms for brain tumor segmentation S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... progression assessment, and overall survival prediction in the BRATS …, 2018 | 138 | 2018 |
| Cell fate coordinates mechano-osmotic forces in intestinal crypt formation Q Yang, SL Xue, CJ Chan, M Rempfler, D Vischi, F Maurer-Gutierrez, ... Nature Cell Biology 23 (7), 733-744, 2021 | 125 | 2021 |
| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge. arXiv preprint … S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv, 1811 | 93 | 1811 |
| Btrfly net: Vertebrae labelling with energy-based adversarial learning of local spine prior A Sekuboyina, M Rempfler, J Kukačka, G Tetteh, A Valentinitsch, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 81 | 2018 |
| Labeling vertebrae with two-dimensional reformations of multidetector CT images: an adversarial approach for incorporating prior knowledge of spine anatomy A Sekuboyina, M Rempfler, A Valentinitsch, BH Menze, JS Kirschke Radiology: Artificial Intelligence 2 (2), e190074, 2020 | 45 | 2020 |
| Textrode-enabled transthoracic electrical bioimpedance measurements–towards wearable applications of impedance cardiography JC Marquez, M Rempfler, F Seoane, K Lindecrantz Journal of Electrical Bioimpedance 4 (1), 45-50, 2013 | 45 | 2013 |
| Verse: a vertebrae labelling and segmentation benchmark A Sekuboyina, A Bayat, ME Husseini, M Löffler, M Rempfler, J Kukačka, ... | 33 | 2020 |
| deepBlink: threshold-independent detection and localization of diffraction-limited spots BT Eichenberger, YX Zhan, M Rempfler, L Giorgetti, JA Chao Nucleic Acids Research 49 (13), 7292-7297, 2021 | 29 | 2021 |
| Reconstructing cerebrovascular networks under local physiological constraints by integer programming M Rempfler, M Schneider, GD Ielacqua, X Xiao, SR Stock, J Klohs, ... Medical image analysis 25 (1), 86-94, 2015 | 29 | 2015 |
| Tracing cell lineages in videos of lens-free microscopy M Rempfler, V Stierle, K Ditzel, S Kumar, P Paulitschke, B Andres, ... Medical image analysis 48, 147-161, 2018 | 25 | 2018 |
| Hierarchical multi-organ segmentation without registration in 3D abdominal CT images V Zografos, A Valentinitsch, M Rempfler, F Tombari, B Menze Medical Computer Vision: Algorithms for Big Data: International Workshop …, 2016 | 25 | 2016 |
| The minimum cost connected subgraph problem in medical image analysis M Rempfler, B Andres, BH Menze Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 21 | 2016 |
| Efficient algorithms for moral lineage tracing M Rempfler, JH Lange, F Jug, C Blasse, EW Myers, BH Menze, B Andres Proceedings of the IEEE International Conference on Computer Vision, 4695-4704, 2017 | 18 | 2017 |
Bjoern H MenzeUniversität ZürichZweryfikowany adres z uzh.ch
