MSCA-UNet: multi-scale channel attention-based UNet for segmentation of medical ultrasound images
Author:
Funder
The National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10586-024-04292-y.pdf
Reference39 articles.
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2. Huang, H.: UNet 3+: A full-scale connected unet for medical image segmentation. In: ICASSP 2020–2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1055–1059. IEEE, New York (2020)
3. Zhou, Z., et al.: Unet++: Redesigning skip connections to exploit multiscale features in image segmentation. IEEE Trans. Med. Imaging. 39(6), 1856–1867 (2019)
4. He, K., et al.: HF-UNet: Learning hierarchically inter-task relevance in multi-task U-Net for accurate prostate segmentation in CT images. In: IEEE Transactions on Medical Imaging, vol. 40 (8), pp. 2118–2128. New York (2021)
5. Pan, H., Zhou, Q., Latecki, L.J.: SGUNET: Semantic Guided UNET for thyroid nodule segmentation. In: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 630–634. IEEE, New York (2021)
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