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Medical image segmentation is a critical task that plays a vital role in diagnosis, treatment planning, and disease monitoring.
Landman, B., Xu, Z., Igelsias, J., Styner, M., Langerak, T., Klein, A.: Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge. In: Proc. MICCAI Multi-Atlas Labeling Beyond Cranial Vault—Workshop Challenge. vol. 5, p. 12 (2015)
2015
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Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. pp. 234–241. Springer (2015)
2015
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Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Proceedings of the European conference on computer vision (ECCV). pp. 801–818 (2018)
2018
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Azad, R., Asadi-Aghbolaghi, M., Fathy, M., Escalera, S.: Bi-directional convlstm u-net with densley connected convolutions. In: Proceedings of the IEEE/CVF international conference on computer vision workshops. pp. 0–0 (2019)
2019
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2019
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Schlemper, J., Oktay, O., Schaap, M., Heinrich, M., Kainz, B., Glocker, B., Rueckert, D.: Attention gated networks: Learning to leverage salient regions in medical images. Medical image analysis 53
2019
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2020
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2020
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2021
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2021
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Fan, H., Xiong, B., Mangalam, K., Li, Y., Yan, Z., Malik, J., Feichtenhofer, C.: Multiscale vision transformers. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 6824–6835 (2021)
2021
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Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin transformer: Hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 10012–10022 (2021)
2021
Cited alongside, same era.
Shen, Z., Zhang, M., Zhao, H., Yi, S., Li, H.: Efficient attention: Attention with linear complexities. In: Proceedings of the IEEE/CVF winter conference on applications of computer vision. pp. 3531–3539 (2021)
2021
Cited alongside, same era.
Valanarasu, J.M.J., Oza, P., Hacihaliloglu, I., Patel, V.M.: Medical transformer: Gated axial-attention for medical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 36–46. Springer (2021)
2021
Cited alongside, same era.
Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J.M., Luo, P.: Segformer: Simple and efficient design for semantic segmentation with transformers. Advances in Neural Information Processing Systems 34
Wang, P., Zheng, W., Chen, T., Wang, Z.: Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice. In: International Conference on Learning Representations (2022), https://openreview.net/forum?id=O476oWmiNNp
2022
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Wang, W., Xie, E., Li, X., Fan, D.P., Song, K., Liang, D., Lu, T., Luo, P., Shao, L.: Pvt v2: Improved baselines with pyramid vision transformer. Computational Visual Media 8
2022
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Wu, H., Chen, S., Chen, G., Wang, W., Lei, B., Wen, Z.: Fat-net: Feature adaptive transformers for automated skin lesion segmentation. Medical Image Analysis 76
2022
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Yao, T., Pan, Y., Li, Y., Ngo, C.W., Mei, T.: Wave-vit: Unifying wavelet and transformers for visual representation learning. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXV. pp. 328–345. Springer (2022)
2022
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2021
Cited alongside, same era.
2021
Cited alongside, same era.
Cao, H., Wang, Y., Chen, J., Jiang, D., Zhang, X., Tian, Q., Wang, M.: Swin-unet: Unet-like pure transformer for medical image segmentation. In: Proceedings of the European Conference on Computer Vision Workshops(ECCVW) (2022)
2022
Cited alongside, same era.
Huang, X., Deng, Z., Li, D., Yuan, X., Fu, Y.: Missformer: An effective transformer for 2d medical image segmentation. IEEE Transactions on Medical Imaging (2022)
2022
Cited alongside, same era.
Ren, P., Li, C., Wang, G., Xiao, Y., Du, Q., Liang, X., Chang, X.: Beyond fixation: Dynamic window visual transformer. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11987–11997 (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Yin, H., Vahdat, A., Alvarez, J.M., Mallya, A., Kautz, J., Molchanov, P.: A-vit: Adaptive tokens for efficient vision transformer. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10809–10818 (2022)
2022
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2023
Closest in time.
Bozorgpour, A., Sadegheih, Y., Kazerouni, A., Azad, R., Merhof, D.: Dermosegdiff: A boundary-aware segmentation diffusion model for skin lesion delineation. In: MICCAI 2023 workshop Prime (2023)
2023
Closest in time.
Heidari, M., Kazerouni, A., Soltany, M., Azad, R., Aghdam, E.K., Cohen-Adad, J., Merhof, D.: Hiformer: Hierarchical multi-scale representations using transformers for medical image segmentation. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 6202–6212 (2023)
2023
Closest in time.
Karimijafarbigloo, S., Azad, R., Merhof, D.: Self-supervised few-shot learning for semantic segmentation: An annotation-free approach. In: MICCAI 2023 workshop (2023)
2023
Closest in time.
Molaei, A., Aminimehr, A., Tavakoli, A., Kazerouni, A., Azad, B., Azad, R., Merhof, D.: Implicit neural representation in medical imaging: A comparative survey. In: ICCV 2023, IEEE International Conference on Computer Vision 2023 (2023)
2023
Closest in time.