Dual Attention Guided R2 U-Net Architecture for Right Ventricle Segmentation in MRI Images-Reference-Cited by-同舟云学术

Dual Attention Guided R2 U-Net Architecture for Right Ventricle Segmentation in MRI Images

Published:2021 Issue: Volume: Page:511-522
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Jiang Lei,Cui Hengfei,Yuwen Chang,Zhang Yanning

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-87358-5_41

Reference20 articles.

1. Jonathan, L., Evan, S., Trevor, D.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431–3440 (2015)

2. 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.) MICCAI 2015. LNCS, vol. 9351, pp. 234–241. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24574-4_28

3. Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: ECCV (2018)

4. He, K., Zhang, X., Ren, S., Sun, J.: Spatial pyramid pooling in deep convolutional networks for visual recognition. In: ECCV (2014)

5. Zhao, H., et al.: Pyramid scene parsing network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimizing Feature Representation via A Nested Network for Object Segmentation;2022 8th International Conference on Optimization and Applications (ICOA);2022-10-06