Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 8 | |
| Section | Intelligent Computing in Healthcare and Bioinformatics | |
| DOI | https://doi.org/10.1051/itmconf/20268401011 | |
| Published online | 06 April 2026 | |
- G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, ... & C. I. Sánchez, A survey on deep learning in medical image anal ysis. Med. Image Anal. 42, 60–88 (2017). [CrossRef] [Google Scholar]
- O. Ronneberger, P. Fischer, & T. Brox, U-net: Convolutional networks for biomedical image segmentation. in Proc. Int. Conf. Med. Image Comput. Comput.-Assist. Intervent. (Springer, Cham, 2015), pp. 234–241. [Google Scholar]
- J. Chen, Y. Lu, Q. Yu, X. Luo, E. Adeli, Y. Wang, ... & Y. Zhou, TransUNet: Transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306 (2021). [Google Scholar]
- H. Huang, L. Lin, R. Tong, H. Hu, Q. Zhang, Y. Iwamoto, ... & J. Wu, UNet 3+: A full-scale connected UNet for medical image segmentation. in ICASSP 2020–2020 IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP) (IEEE, 2020), pp. 1055–1059. [Google Scholar]
- A. Hatamizadeh, Y. Tang, V. Nath, D. Yang, A. Myronenko, B. Landman, ... & D. Xu, UNETR: Transformers for 3D medical image segmentation. in Proc. IEEE/CVF Winter Conf. Appl. Comput. Vis. (IEEE, 2022), pp. 574–584. [Google Scholar]
- H. Cao, Y. Wang, J. Chen, D. Jiang, X. Zhang, Q. Tian, & M. Wang, Swin-Unet: UNet-like pure transformer for medical image segmentation. in Proc. Eur. Conf. Comput. Vis. (Springer, Cham, 2022), pp. 205–218. [Google Scholar]
- H. Wang, P. Cao, J. Wang, & O. R. Zaiane, UCTransNet: Rethinking the skip connections in U-Net from a channel-wise perspective with transformer. in Proc. AAAI Conf. Artif. Intell. 36(3), 2441–2449 (2022). [Google Scholar]
- A. Dosovitskiy, An image is worth 16×16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020). [Google Scholar]
- B. Koonce, ResNet 50. In Convolutional Neural Networks with Swift for TensorFlow: Image Recognition and Dataset Categorization (Apress, Berkeley, CA, 2021), pp. 63–72. [Google Scholar]
- B. Li, D. Lima, Facial expression recognition via ResNet-50. International Journal of Cognitive Computing in Engineering 2, 57–64 (2021). [Google Scholar]
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