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Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.

Y. He, G. Yang, J. Yang, Y. Chen, Y. Kong, J. Wu, L. Tang, X. Zhu, J. Dillenseger, P. Shao, S. Zhang, H. Shu, J. Coatrieux, and S. Li. Medical Image Anal., (2020)

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Lijun Tang

Lijun Cai

Tang Tang

Lijun Yao

Lijun Zhu

Other publications of authors with the same name

Entropy evolution of field interacting with V-type three-level atom via intensity-dependent couplingC. Huang, L. Tang, F. Kong, J. Fang, and M. Zhou. Physica A: Statistical Mechanics and its Applications, 368 (1): 25--30 (Aug 1, 2006)Survey of Research on Named Entity Recognition in Cyber Threat Intelligence.K. Zhang, X. Chen, Y. Jing, S. Wang, and L. Tang. SmartCloud, page 68-73. IEEE, (2022)Automatic Segmentation of Kidney and Renal Tumor in CT Images Based on 3D Fully Convolutional Neural Network with Pyramid Pooling Module.G. Yang, G. Li, T. Pan, Y. Kong, J. Wu, H. Shu, L. Luo, J. Dillenseger, J. Coatrieux, L. Tang and 1 other author(s). ICPR, page 3790-3795. IEEE Computer Society, (2018)Designing an intelligent user interface for instructional video indexing and browsing.L. Tang, and J. Kender. IUI, page 318-320. ACM, (2006)Unsupervised Three-Dimensional Image Registration Using a Cycle Convolutional Neural Network.Z. Lu, J. Coatrieux, G. Yang, T. Hua, L. Hu, Y. Kong, L. Tang, X. Zhu, J. Dillenseger, and H. Shu. ICIP, page 2174-2178. IEEE, (2019)A Multi-Task Convolutional Neural Network for Renal Tumor Segmentation and Classification Using Multi-Phasic CT Images.T. Pan, H. Shu, J. Coatrieux, G. Yang, C. Wang, Z. Lu, Z. Zhou, Y. Kong, L. Tang, X. Zhu and 1 other author(s). ICIP, page 809-813. IEEE, (2019)Heart Modeling by Convexity Preserving Segmentation and Convex Shape Decomposition.X. Shi, L. Tang, S. Zhang, and C. Li. ISVC, volume 11241 of Lecture Notes in Computer Science, page 34-43. Springer, (2018)Quasi-linear modeling of gyroresonance between different MLT chorus and geostationary orbit electrons.Z. Zhang, F. Xiao, Y. He, Z. He, C. Yang, X. Zhou, and L. Tang. Sci. China Inf. Sci., 55 (11): 2624-2634 (2012)Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.Y. He, G. Yang, J. Yang, Y. Chen, Y. Kong, J. Wu, L. Tang, X. Zhu, J. Dillenseger, P. Shao and 4 other author(s). Medical Image Anal., (2020)Adoption of Machine Learning Algorithm-Based Intelligent Basketball Training Robot in Athlete Injury Prevention.T. Xu, and L. Tang. Frontiers Neurorobotics, (2020)

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Disambiguation of "Tang, Lijun"

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Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.

Please choose a person to relate this publication to

Lijun Tang

Lijun Cai

Tang Tang

Lijun Yao

Lijun Zhu

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tang, Lijun"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.

Please choose a person to relate this publication to

Lijun Tang

Lijun Cai

Tang Tang

Lijun Yao

Lijun Zhu

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.