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Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images Through Recurrent Attention.

J. bin Huang, E. Zhuo, H. Li, L. Liu, H. Cai, and Y. Ou. MICCAI (5), volume 11768 of Lecture Notes in Computer Science, page 494-502. Springer, (2019)

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Lizhi Zhu

Lizhi Zhang

Lizhi Zheng

Liu Liu

Other publications of authors with the same name

Superpixel-Based Segmentation for 3D Prostate MR Images.Z. Tian, L. Liu, Z. Zhang, and B. Fei. IEEE Trans. Med. Imaging, 35 (3): 791-801 (2016)Tracking control for the dynamic links of discrete-time complex dynamical network via state observer.L. Liu, Y. Wang, and Z. Gao. Appl. Math. Comput., (2020)A semiautomatic approach for prostate segmentation in MR images using local texture classification and statistical shape modeling.M. Shahedi, M. Halicek, Q. Li, L. Liu, Z. Zhang, S. Verma, D. Schuster, and B. Fei. Medical Imaging: Image-Guided Procedures, volume 10951 of SPIE Proceedings, page 109512I. SPIE, (2019)A Lightweight High-Resolution Remote Sensing Image Cultivated Land Extraction Method Integrating Transfer Learning and SENet.L. Li, Z. Chen, Y. Ma, and L. Liu. IEEE Access, (2024)A fully automatic multi-atlas based segmentation method for prostate MR images.Z. Tian, L. Liu, and B. Fei. Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 941340. SPIE, (2015)A supervoxel-based segmentation method for prostate MR images.Z. Tian, L. Liu, and B. Fei. Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 941318. SPIE, (2015)Adaptive Control of the Structural Balance for a Class of Complex Dynamical Networks.Z. Gao, Y. Wang, Y. Peng, L. Liu, and H. Chen. J. Syst. Sci. Complex., 33 (3): 725-742 (2020)Segmentation and Registration of the Liver in Dynamic Contrast-Enhanced Computed Tomography Images.S. Ren, L. Zhan, S. Chen, H. Dai, G. Ruan, S. Li, L. Liu, R. Lin, and H. Chen. J. Medical Imaging Health Informatics, 11 (3): 773-780 (2021)PM2.5 concentration prediction model based on SA-LSTM.Z. Wang, and L. Liu. AISNS, page 68-71. ACM, (2023)Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images Through Recurrent Attention.J. bin Huang, E. Zhuo, H. Li, L. Liu, H. Cai, and Y. Ou. MICCAI (5), volume 11768 of Lecture Notes in Computer Science, page 494-502. Springer, (2019)

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Disambiguation of "Liu, Lizhi"

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Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images Through Recurrent Attention.

Please choose a person to relate this publication to

Lizhi Zhu

Lizhi Zhang

Lizhi Zheng

Liu Liu

Liu Liu

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Liu, Lizhi"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images Through Recurrent Attention.

Please choose a person to relate this publication to

Lizhi Zhu

Lizhi Zhang

Lizhi Zheng

Liu Liu

Liu Liu

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images Through Recurrent Attention.