MTA-Net: A Multi-task Assisted Network for Whole-Body Lymphoma Segmentation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63211-2_14
Reference20 articles.
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3. Chen, J., et al.: Transunet: transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306 (2021)
4. Chen, Y., Dai, X., Liu, M., Chen, D., Yuan, L., Liu, Z.: Dynamic convolution: attention over convolution kernels. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 11030–11039 (2020)
5. Desbordes, P., Petitjean, C., Ruan, S.: 3d automated lymphoma segmentation in pet images based on cellular automata. In: 2014 4th International Conference on Image Processing Theory, Tools and Applications (IPTA), pp. 1–6. IEEE (2014)
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