| The multimodal brain tumor image segmentation benchmark (BRATS) BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ... IEEE transactions on medical imaging 34 (10), 1993-2024, 2014 | 4190 | 2014 |
| Decision forests: A unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning A Criminisi, J Shotton, E Konukoglu Foundations and trends® in computer graphics and vision 7 (2–3), 81-227, 2012 | 1401 | 2012 |
| Regression forests for efficient anatomy detection and localization in computed tomography scans A Criminisi, D Robertson, E Konukoglu, J Shotton, S Pathak, S White, ... Medical image analysis 17 (8), 1293-1303, 2013 | 629 | 2013 |
| Shape-based hand recognition E Yoruk, E Konukoglu, B Sankur, J Darbon IEEE transactions on image processing 15 (7), 1803-1815, 2006 | 412 | 2006 |
| Decision forests for tissue-specific segmentation of high-grade gliomas in multi-channel MR. D Zikic, B Glocker, E Konukoglu, A Criminisi, C Demiralp, J Shotton, ... MICCAI (3), 369-376, 2012 | 332 | 2012 |
| 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 57 (2), 378-390, 2011 | 290 | 2011 |
| Contrastive learning of global and local features for medical image segmentation with limited annotations K Chaitanya, E Erdil, N Karani, E Konukoglu Advances in Neural Information Processing Systems 33, 12546-12558, 2020 | 281 | 2020 |
| An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation CF Baumgartner, LM Koch, M Pollefeys, E Konukoglu Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 240 | 2018 |
| Unsupervised detection of lesions in brain MRI using constrained adversarial auto-encoders X Chen, E Konukoglu arXiv preprint arXiv:1806.04972, 2018 | 238 | 2018 |
| Exploring cross-image pixel contrast for semantic segmentation W Wang, T Zhou, F Yu, J Dai, E Konukoglu, L Van Gool Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 222 | 2021 |
| Image guided personalization of reaction-diffusion type tumor growth models using modified anisotropic eikonal equations E Konukoglu, O Clatz, BH Menze, B Stieltjes, MA Weber, E Mandonnet, ... IEEE transactions on medical imaging 29 (1), 77-95, 2009 | 216 | 2009 |
| Automatic localization and identification of vertebrae in arbitrary field-of-view CT scans B Glocker, J Feulner, A Criminisi, DR Haynor, E Konukoglu Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th …, 2012 | 210 | 2012 |
| Vertebrae localization in pathological spine CT via dense classification from sparse annotations B Glocker, D Zikic, E Konukoglu, DR Haynor, A Criminisi Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 180 | 2013 |
| Clinical prediction from structural brain MRI scans: a large-scale empirical study MR Sabuncu, E Konukoglu, Alzheimer’s Disease Neuroimaging Initiative Neuroinformatics 13, 31-46, 2015 | 161 | 2015 |
| Glioma dynamics and computational models: a review of segmentation, registration, and in silico growth algorithms and their clinical applications ED Angelini, O Clatz, E Mandonnet, E Konukoglu, L Capelle, H Duffau Current Medical Imaging 3 (4), 262-276, 2007 | 161 | 2007 |
| Is synthesizing MRI contrast useful for inter-modality analysis? JE Iglesias, E Konukoglu, D Zikic, B Glocker, K Van Leemput, B Fischl Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 150 | 2013 |
| Phiseg: Capturing uncertainty in medical image segmentation CF Baumgartner, KC Tezcan, K Chaitanya, AM Hötker, UJ Muehlematter, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 146 | 2019 |
| Extrapolating glioma invasion margin in brain magnetic resonance images: Suggesting new irradiation margins E Konukoglu, O Clatz, PY Bondiau, H Delingette, N Ayache Medical image analysis 14 (2), 111-125, 2010 | 144 | 2010 |
| Semi-supervised and task-driven data augmentation K Chaitanya, N Karani, CF Baumgartner, A Becker, O Donati, ... Information Processing in Medical Imaging: 26th International Conference …, 2019 | 130 | 2019 |
| Visual feature attribution using wasserstein gans CF Baumgartner, LM Koch, KC Tezcan, JX Ang, E Konukoglu Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 129 | 2018 |
Antonio CriminisiPartner Research Lead at Microsoft CorporationE-mailová adresa ověřena na: microsoft.com
