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Calibration and Distraction Mining Network for Aortic True Lumen segmentation.

X. Fan, S. Tian, L. Yu, M. Han, L. Liu, J. Cheng, W. Wu, X. Kang, и D. Zhang. J. Intell. Fuzzy Syst., 43 (6): 7863-7875 (2022)

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Cheng-Yung Cheng

Ying Min Cheng

I-Fen Cheng

Xuerong Cheng

Yao Cheng

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Multi-Attention Mechanism Medical Image Segmentation Combined with Word Embedding Technology.J. Cheng, S. Tian, L. Yu, и H. You. Autom. Control. Comput. Sci., 54 (6): 560-571 (2020)DCACNet: Dual context aggregation and attention-guided cross deconvolution network for medical image segmentation.H. Lu, S. Tian, L. Yu, L. Liu, J. Cheng, W. Wu, X. Kang, и D. Zhang. Comput. Methods Programs Biomed., (2022)SAM-Med2D.J. Cheng, J. Ye, Z. Deng, J. Chen, T. Li, H. Wang, Y. Su, Z. Huang, J. Chen, L. Jiang и 5 other автор(ы). CoRR, (2023)SAM-Med3D.H. Wang, S. Guo, J. Ye, Z. Deng, J. Cheng, T. Li, J. Chen, Y. Su, Z. Huang, Y. Shen и 4 other автор(ы). CoRR, (2023)PRFNet: Progressive Region Focusing Network for Polyp Segmentation.J. Chen, J. Cheng, L. Jiang, P. Yin, G. Wang, и M. Zhu. PRCV (5), том 14429 из Lecture Notes in Computer Science, стр. 394-406. Springer, (2023)SegNetr: Rethinking the Local-Global Interactions and Skip Connections in U-Shaped Networks.J. Cheng, C. Gao, F. Wang, и M. Zhu. MICCAI (6), том 14225 из Lecture Notes in Computer Science, стр. 64-74. Springer, (2023)LatLRR-CNN: an infrared and visible image fusion method combining latent low-rank representation and CNN.Y. Yang, C. Gao, Z. Ming, J. Guo, E. Leopold, J. Cheng, J. Zuo, и M. Zhu. Multim. Tools Appl., 82 (23): 36303-36323 (сентября 2023)A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation.Z. Huang, Z. Deng, J. Ye, H. Wang, Y. Su, T. Li, H. Sun, J. Cheng, J. Chen, J. He и 4 other автор(ы). CoRR, (2023)SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks.J. Ye, J. Cheng, J. Chen, Z. Deng, T. Li, H. Wang, Y. Su, Z. Huang, J. Chen, L. Jiang и 5 other автор(ы). CoRR, (2023)SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation.G. Wang, J. Ye, J. Cheng, T. Li, Z. Chen, J. Cai, J. He, и B. Zhuang. CoRR, (2024)

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