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Yefeng Zheng
Yefeng Zheng
Tencent, Shenzhen, China
Bestätigte E-Mail-Adresse bei tencent.com - Startseite
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Zitiert von
Zitiert von
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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
7242008
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
3742006
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
3442018
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
2702004
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
2582008
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
2222007
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
2052017
Hierarchical, learning-based automatic liver segmentation
H Ling, SK Zhou, Y Zheng, B Georgescu, M Suehling, D Comaniciu
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
1952008
Med3D: Transfer Learning for 3D Medical Image Analysis
S Chen, K Ma, Y Zheng
arXiv preprint arXiv:1904.00625, 2019
1862019
3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data
Y Zheng, D Liu, B Georgescu, H Nguyen, D Comaniciu
MICCAI, 2015
1782015
Method and system for comprehensive patient-specific modeling of the heart
RI Ionasec, I Voigt, V Mihalef, S Grbic, D Vitanovski, Y Wang, Y Zheng, ...
US Patent 8,682,626, 2014
1712014
Deep similarity learning for multimodal medical images
X Cheng, L Zhang, Y Zheng
Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018
1682018
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
1572016
Marginal space deep learning: Efficient architecture for volumetric image parsing
FC Ghesu, E Krubasik, B Georgescu, V Singh, Y Zheng, J Hornegger, ...
IEEE transactions on medical imaging 35 (5), 1217-1228, 2016
1552016
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
1482019
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
1462017
Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets
C Tobon-Gomez, AJ Geers, J Peters, J Weese, K Pinto, R Karim, ...
IEEE transactions on medical imaging 34 (7), 1460-1473, 2015
1432015
Spine detection in CT and MR using iterated marginal space learning
BM Kelm, M Wels, SK Zhou, S Seifert, M Suehling, Y Zheng, D Comaniciu
Medical image analysis 17 (8), 1283-1292, 2013
1302013
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
1282015
Method and system for anatomical object detection using marginal space deep neural networks
B Georgescu, Y Zheng, H Nguyen, VK Singh, D Comaniciu, D Liu
US Patent 9,668,699, 2017
1162017
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