| The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) B Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ... IEEE Transactions on Medical Imaging 34 (10), 1993 - 2024, 2015 | 6655 | 2015 |
| Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge BM Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus ... arXiv preprint arXiv:1811.02629, 2018 | 2333 | 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 | 1427 | 2023 |
| A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data BH Menze, BM Kelm, R Masuch, U Himmelreich, P Bachert, W Petrich, ... BMC Bioinformatics 10 (1), 213, 2009 | 1405 | 2009 |
| The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature communications 13 (1), 4128, 2022 | 1160 | 2022 |
| 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 | 1156 | 2019 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 899 | 2021 |
| 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 | 860 | 2016 |
| ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI O Maier, BH Menze, J Von der Gablentz, L Häni, MP Heinrich, M Liebrand, ... Medical image analysis 35, 250-269, 2017 | 554 | 2017 |
| 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 | 468 | 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 | 457 | 2017 |
| Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ... IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021 | 415 | 2021 |
| Why rankings of biomedical image analysis competitions should be interpreted with care L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ... Nature communications 9 (1), 5217, 2018 | 352 | 2018 |
| 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 | 339* | 2021 |
| On oblique random forests BH Menze, BM Kelm, D Splitthoff, U Koethe, F Hamprecht European Conference on Machine Learning (ECML PKDD), 453-469, 2011 | 337 | 2011 |
| 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 | 335 | 2020 |
| 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 | 331* | 2024 |
| Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images E Geremia, O Clatz, BH Menze, E Konukoglu, A Criminisi, N Ayache NeuroImage, 2011 | 321 | 2011 |
| clDice-a novel topology-preserving loss function for tubular structure segmentation S Shit, JC Paetzold, A Sekuboyina, I Ezhov, A Unger, A Zhylka, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 317 | 2021 |
| A generative model for brain tumor segmentation in multi-modal images BH Menze, K Van Leemput, D Lashkari, MA Weber, N Ayache, P Golland Medical Image Computing and Computer-Assisted Intervention (MICCAI), 151-159, 2010 | 310 | 2010 |
Bene WiestlerAI for Image-Guided Diagnosis and Therapy, TUMVerified email at tum.de
