| 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 | 2146 | 2018 |
| The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature Communications 13 (1), 1-13, 2022 | 1068 | 2022 |
| Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features Y Zheng, A Barbu, B Georgescu, M Scheuering, D Comaniciu IEEE transactions on medical imaging 27 (11), 1668-1681, 2008 | 773 | 2008 |
| Med3D: Transfer Learning for 3D Medical Image Analysis S Chen, K Ma, Y Zheng arXiv preprint arXiv:1904.00625, 2019 | 571 | 2019 |
| Translating and segmenting multimodal medical volumes with cycle-and shapeconsistency generative adversarial network Z Zhang, L Yang, Y Zheng Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 524 | 2018 |
| Combo loss: Handling input and output imbalance in multi-organ segmentation SA Taghanaki, Y Zheng, SK Zhou, B Georgescu, P Sharma, D Xu, ... Computerized Medical Imaging and Graphics 75, 24-33, 2019 | 417 | 2019 |
| Robust point matching for nonrigid shapes by preserving local neighborhood structures Y Zheng, D Doermann IEEE transactions on pattern analysis and machine intelligence 28 (4), 643-649, 2006 | 390 | 2006 |
| Multi-scale deep reinforcement learning for real-time 3D-landmark detection in CT scans FC Ghesu, B Georgescu, Y Zheng, S Grbic, A Maier, J Hornegger, ... IEEE transactions on pattern analysis and machine intelligence 41 (1), 176-189, 2017 | 348 | 2017 |
| A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging Z Xiong, Q Xia, Z Hu, N Huang, C Bian, Y Zheng, S Vesal, N Ravikumar, ... Medical Image Analysis 67, 101832, 2021 | 340 | 2021 |
| Method and System for Anatomical Object Detection Using Marginal Space Deep Neural Networks B Georgescu, Y Zheng, H Hguyen, VK Singh, D Comaniciu, D Liu US Patent 20,160,174,902, 2016 | 300 | 2016 |
| Script-independent text line segmentation in freestyle handwritten documents Y Li, Y Zheng, D Doermann, S Jaeger IEEE Transactions on Pattern Analysis and Machine Intelligence 30 (8), 1313-1329, 2008 | 287 | 2008 |
| Machine printed text and handwriting identification in noisy document images Y Zheng, H Li, D Doermann IEEE transactions on pattern analysis and machine intelligence 26 (3), 337-353, 2004 | 287 | 2004 |
| Morphological diversity of single neurons in molecularly defined cell types H Peng, P Xie, L Liu, X Kuang, Y Wang, L Qu, H Gong, S Jiang, A Li, ... Nature 598 (7879), 174-181, 2021 | 282 | 2021 |
| Calibrated RGB-D Salient Object Detection W Ji, J Li, S Yu, M Zhang, Y Piao, S Yao, Q Bi, K Ma, Y Zheng, H Lu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 272 | 2021 |
| X2CT-GAN: reconstructing CT from biplanar X-rays with generative adversarial networks X Ying, H Guo, K Ma, J Wu, Z Weng, Y Zheng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 272 | 2019 |
| Deep similarity learning for multimodal medical images X Cheng, L Zhang, Y Zheng Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018 | 248 | 2018 |
| Method and System for Machine Learning Based Assessment of Fractional Flow Reserve P Sharma, A Kamen, B Georgescu, F Sauer, D Comaniciu, Y Zheng, ... US Patent 20,150,112,182, 2015 | 244 | 2015 |
| Deep learning and convolutional neural networks for medical image computing L Lu, Y Zheng, G Carneiro, L Yang Advances in Computer Vision and Pattern Recognition 10, 978-3, 2017 | 232 | 2017 |
| 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data Y Zheng, D Liu, B Georgescu, H Nguyen, D Comaniciu MICCAI, 2015 | 230 | 2015 |
| Fast automatic heart chamber segmentation from 3D CT data using marginal space learning and steerable features Y Zheng, A Barbu, B Georgescu, M Scheuering, D Comaniciu 2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007 | 230 | 2007 |
Dorin ComaniciuSiemens HealthineersE-mailová adresa ověřena na: siemens-healthineers.com
