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Cited by in F6Publishing
For: Fang Y, Huang H, Yang W, Xu X, Jiang W, Lai X. Nonlocal convolutional block attention module VNet for gliomas automatic segmentation. Int J Imaging Syst Tech 2022;32:528-43. [DOI: 10.1002/ima.22639] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Li Q, Liu X, He Y, Li D, Xue J. Temperature guided network for 3D joint segmentation of the pancreas and tumors. Neural Networks 2022. [DOI: 10.1016/j.neunet.2022.10.026] [Reference Citation Analysis]
2 Wang L, Cai L, Chen C, Fu X, Yu J, Ge R, Yuan B, Yang X, Shao Q, Lv Q. A novel DAVnet3+ method for precise segmentation of bladder cancer in MRI. Vis Comput 2022. [DOI: 10.1007/s00371-022-02622-y] [Reference Citation Analysis]
3 Xiaoyu F, Linlin W, Chang L, Tao H. An Improved Method of Image Recognition with Deep Learning Combined with Attention Mechanism. 2022 7th International Conference on Image, Vision and Computing (ICIVC) 2022. [DOI: 10.1109/icivc55077.2022.9887045] [Reference Citation Analysis]
4 Tene-hurtado D, Almeida-galárraga DA, Villalba-meneses G, Alvarado-cando O, Cadena-morejón C, Salazar VH, Orozco-lópez O, Tirado-espín A. Brain Tumor Segmentation Based on 2D U-Net Using MRI Multi-modalities Brain Images. Smart Technologies, Systems and Applications 2022. [DOI: 10.1007/978-3-030-99170-8_25] [Reference Citation Analysis]
5 Liu D, Sheng N, He T, Wang W, Zhang J, Zhang J. . MBE 2022;19:5576-90. [DOI: 10.3934/mbe.2022261] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Zhang J, Jiang Z, Liu D, Sun Q, Hou Y, Liu B. 3D asymmetric expectation-maximization attention network for brain tumor segmentation. NMR Biomed 2021;:e4657. [PMID: 34859922 DOI: 10.1002/nbm.4657] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]