| 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 | 1407 | 2023 |
| Machine learning analysis of whole mouse brain vasculature MI Todorov*, JC Paetzold*, O Schoppe, G Tetteh, S Shit, V Efremov, ... Nature Methods 17 (4), 442-449, 2020 | 349* | 2020 |
| clDice - a Topology-Preserving Loss Function for Tubular Structure Segmentation S Shit*, JC Paetzold*, A Sekuboyina, A Zhylka, I Ezhov, A Unger, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 329* | 2021 |
| 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 | 296 | 2021 |
| Cellular and molecular probing of intact human organs S Zhao, MI Todorov, R Cai, AIM Rami, H Steinke, E Kemter, H Mai, ... Cell 180 (4), 796-812. e19, 2020 | 268 | 2020 |
| An automatic multi-tissue human fetal brain segmentation benchmark using the fetal tissue annotation dataset K Payette, P de Dumast, H Kebiri, I Ezhov, JC Paetzold, S Shit, A Iqbal, ... Scientific data 8 (1), 167, 2021 | 136* | 2021 |
| DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis BM Hongwei Li*, Johannes C. Paetzold*, Anjany Sekuboyina, Florian Kofler ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 103* | 2019 |
| Distinct molecular profiles of skull bone marrow in health and neurological disorders ZI Kolabas, LB Kuemmerle, R Perneczky, B Förstera, S Ulukaya, M Ali, ... Cell 186 (17), 3706-3725. e29, 2023 | 81 | 2023 |
| Shape-aware complementary-task learning for multi-organ segmentation F Navarro, S Shit, I Ezhov, J Paetzold, A Gafita, JC Peeken, SE Combs, ... Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019 | 80* | 2019 |
| Spatial proteomics in three-dimensional intact specimens HS Bhatia, AD Brunner, F Öztürk, S Kapoor, Z Rong, H Mai, M Thielert, ... Cell 185 (26), 5040-5058. e19, 2022 | 78* | 2022 |
| Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective. AB Qasim, I Ezhov, S Shit, O Schoppe, JC Paetzold, A Sekuboyina, ... Medical imaging with deep learning, 655-668, 2020 | 74* | 2020 |
| Whole-body cellular mapping in mouse using standard IgG antibodies H Mai, J Luo, L Hoeher, R Al-Maskari, I Horvath, Y Chen, F Kofler, ... Nature Biotechnology 42 (4), 617-627, 2024 | 67 | 2024 |
| Relationformer: A Unified Framework for Image-to-Graph Generation S Shit, R Koner, B Wittmann, J Paetzold, I Ezhov, H Li, J Pan, ... ECCV 2022, 2022 | 65 | 2022 |
| Topologically faithful image segmentation via induced matching of persistence barcodes N Stucki*, JC Paetzold*, S Shit*, B Menze, U Bauer International Conference on Machine Learning, 32698-32727, 2023 | 52* | 2023 |
| Anthropogenic CO2 emissions assessment of Nile Delta using XCO2 and SIF data from OCO-2 satellite A Shekhar, J Chen, JC Paetzold, F Dietrich, X Zhao, S Bhattacharjee, ... Environmental Research Letters 15 (9), 095010, 2020 | 50 | 2020 |
| 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 | 47 | 2021 |
| Differentially private graph neural networks for whole-graph classification TT Mueller, JC Paetzold, C Prabhakar, D Usynin, D Rueckert, G Kaissis IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7308-7318, 2022 | 44 | 2022 |
| Whole brain vessel graphs: A dataset and benchmark for graph learning and neuroscience JC Paetzold, J McGinnis, S Shit, I Ezhov, P Büschl, C Prabhakar, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 42* | 2021 |
| Verse: a vertebrae labelling and segmentation benchmark A Sekuboyina, A Bayat, ME Husseini, M Löffler, M Rempfler, J Kukačka, ... | 40 | 2020 |
| Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework TS Jones, JE Franklin, J Chen, F Dietrich, KD Hajny, JC Paetzold, ... Atmospheric Chemistry and Physics 21 (17), 13131-13147, 2021 | 39* | 2021 |
Bjoern MenzeUniversität ZürichВерификована је имејл адреса на uzh.ch