Author:
Fan Yazhuo,Song Jianhua,Yuan Lei,Jia Yunlin
Publisher
Springer Science and Business Media LLC
Reference45 articles.
1. Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) Medical image computing and computer-assisted intervention—MICCAI 2015, pp. 234–241. Springer, Cham (2015)
2. Milletari, F., Navab, N., Ahmadi, S.-A.: V-Net: fully convolutional neural networks for volumetric medical image segmentation. In: 2016 Fourth International Conference on 3D Vision 3DV. Pp. 565–571 (2016). https://doi.org/10.1109/3DV.2016.79
3. Zhou, Z., Rahman Siddiquee, M.M., Tajbakhsh, N., Liang, J.: UNet++: a nested U-Net architecture for medical image segmentation. Comput. Vis. Pattern Recogn. 11045, 3–11 (2018). https://doi.org/10.1007/978-3-030-00889-5_1
4. Huang, H., Lin, L., Tong, R., Hu, H., Zhang, Q., Iwamoto, Y., Han, X., Chen, Y.-W., Wu, J.: UNet 3+: A full-scale connected UNet for medical image segmentation. In: ICASSP 2020—2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 1055–1059 (2020)
5. Yuan, L., Song, J., Fan, Y.: FM-Unet: biomedical image segmentation based on feedback mechanism Unet. Math. Biosci. Eng. 20, 12039–12055 (2023). https://doi.org/10.3934/mbe.2023535