| 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 | 1166 | 2023 |
| Metrics reloaded: recommendations for image analysis validation L Maier-Hein, A Reinke, P Godau, MD Tizabi, F Buettner, E Christodoulou, ... Nature methods 21 (2), 195-212, 2024 | 215* | 2024 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 185 | 2022 |
| Common limitations of image processing metrics: A picture story A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ... arXiv preprint arXiv:2104.05642, 2021 | 172 | 2021 |
| 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, 125, 2020 | 95 | 2020 |
| DiamondGAN: unified multi-modal generative adversarial networks for MRI sequences synthesis H Li, JC Paetzold, A Sekuboyina, F Kofler, J Zhang, JS Kirschke, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 93 | 2019 |
| ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset MR Hernandez Petzsche, E de la Rosa, U Hanning, R Wiest, ... Scientific data 9 (1), 762, 2022 | 88 | 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 | 58* | 2020 |
| Understanding metric-related pitfalls in image analysis validation A Reinke, MD Tizabi, M Baumgartner, M Eisenmann, D Heckmann-Nötzel, ... Nature methods 21 (2), 182-194, 2024 | 57 | 2024 |
| 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 | 53 | 2022 |
| 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 | 51* | 2021 |
| The brain tumor sequence registration challenge: establishing correspondence between pre-operative and follow-up MRI scans of diffuse glioma patients B Baheti, D Waldmannstetter, S Chakrabarty, H Akbari, M Bilello, ... arXiv preprint arXiv:2112.06979, 2021 | 45 | 2021 |
| The brain tumor segmentation (BRATS) challenge 2023: Focus on pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs) AF Kazerooni, N Khalili, X Liu, D Haldar, Z Jiang, SM Anwar, J Albrecht, ... arXiv preprint arXiv:2305.17033, 2023 | 41 | 2023 |
| 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 | 37 | 2024 |
| The brain tumor segmentation (brats) challenge 2023: glioma segmentation in sub-saharan Africa patient population (brats-africa) M Adewole, JD Rudie, A Gbdamosi, O Toyobo, C Raymond, D Zhang, ... ArXiv, 2023 | 32 | 2023 |
| Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging CM Pirkl, L Nunez-Gonzalez, F Kofler, S Endt, L Grundl, M Golbabaee, ... Neuroradiology, 1-21, 2021 | 32 | 2021 |
| Improving automated glioma segmentation in routine clinical use through artificial intelligence-based replacement of missing sequences with synthetic magnetic resonance imaging … MF Thomas, F Kofler, L Grundl, T Finck, H Li, C Zimmer, B Menze, ... Investigative Radiology 57 (3), 187-193, 2022 | 31 | 2022 |
| The brain tumor segmentation (BraTS-METS) challenge 2023: Brain metastasis segmentation on pre-treatment MRI AW Moawad, A Janas, U Baid, D Ramakrishnan, L Jekel, K Krantchev, ... arXiv preprint arXiv:2306.00838, 2023 | 27 | 2023 |
| Fully automated analysis combining [18F]-FET-PET and multiparametric MRI including DSC perfusion and APTw imaging: a promising tool for objective evaluation of glioma progression KJ Paprottka, S Kleiner, C Preibisch, F Kofler, F Schmidt-Graf, ... European journal of nuclear medicine and molecular imaging 48 (13), 4445-4455, 2021 | 24 | 2021 |
| Immunohistochemically characterized intratumoral heterogeneity is a prognostic marker in human glioblastoma F Liesche-Starnecker, K Mayer, F Kofler, S Baur, F Schmidt-Graf, ... Cancers 12 (10), 2964, 2020 | 24 | 2020 |
Bjoern H MenzeUniversität ZürichVerified email at uzh.ch
