The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
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Citations
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al. (2020) · arXiv · doi:10.48550/arxiv.2010.11929 · Cited by 47,472
CBAM: Convolutional Block Attention Module
Woo, S., Park, J., Lee, J.-Y., & Kweon, I. S. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_1 · Cited by 25,853
Zhao, H., Shi, J., Qi, X., Wang, X., & Jia, J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.660 · Cited by 16,438
Wang, X., Girshick, R., Gupta, A., & He, K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00813 · Cited by 11,596
Identity mappings in deep residual networks
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46493-0_38 · Cited by 10,741
Identity Mappings in Deep Residual Networks
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · arXiv · doi:10.48550/arxiv.1603.05027 · Cited by 10,665
nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., & Maier-Hein, K. H. (2021) · Nature Methods · doi:10.1038/s41592-020-01008-z · Cited by 10,477
Cited by
H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmentation
He, A., Wang, K., Li, T., Du, C., Xia, S., & Fu, H. (2023) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3264513 · Cited by 399
M3T: three-dimensional Medical image classifier using Multi-plane and Multi-slice Transformer
Jang, J., & Hwang, D. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.02006 · Cited by 133
A survey on deep learning in medical ultrasound imaging
Song, K., Feng, J., & Chen, D. (2024) · Frontiers in Physics · doi:10.3389/fphy.2024.1398393 · Cited by 59
Metadata
- Authors
- Gao, Y., Zhou, M., & Metaxas, D. N.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2021
- Pages
- 61-71
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3204614423
- Cited by
- 513
- References
- 30
- FWCI
- 27.46
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation. https://app.cochat.ai/papers/10.1007/978-3-030-87199-4_6
- The paper
- Gao, Y., Zhou, M., & Metaxas, D. N. (2021). UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-87199-4_6
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
