Vol. 18, No. 7, July 31, 2024
10.3837/tiis.2024.07.001,
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Abstract
The unique U-shaped structure of U-Net network makes it achieve good performance in image segmentation. This network is a lightweight network with a small number of parameters for small image segmentation datasets. However, when the medical image to be segmented contains a lot of detailed information, the segmentation results cannot fully meet the actual requirements. In order to achieve higher accuracy of medical image segmentation, a novel improved U-Net network architecture called multi-scale encoder-decoder U-Net+ (MEDU-Net+) is proposed in this paper. We design the GoogLeNet for achieving more information at the encoder of the proposed MEDU-Net+, and present the multi-scale feature extraction for fusing semantic information of different scales in the encoder and decoder. Meanwhile, we also introduce the layer-by-layer skip connection to connect the information of each layer, so that there is no need to encode the last layer and return the information. The proposed MEDU-Net+ divides the unknown depth network into each part of deconvolution layer to replace the direct connection of the encoder and decoder in U-Net. In addition, a new combined loss function is proposed to extract more edge information by combining the advantages of the generalized dice and the focal loss functions. Finally, we validate our proposed MEDU-Net+ and other classic medical image segmentation networks on three medical image datasets. The experimental results show that our proposed MEDU-Net+ has prominent superior performance compared with other medical image segmentation networks.
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Cite this article
[IEEE Style]
Z. Yang, X. Sun, Y. Yang, X. Wu, "MEDU-Net+: a novel improved U-Net based on multi-scale encoder-decoder for medical image segmentation," KSII Transactions on Internet and Information Systems, vol. 18, no. 7, pp. 1706-1725, 2024. DOI: 10.3837/tiis.2024.07.001.
[ACM Style]
Zhenzhen Yang, Xue Sun, Yongpeng Yang, and Xinyi Wu. 2024. MEDU-Net+: a novel improved U-Net based on multi-scale encoder-decoder for medical image segmentation. KSII Transactions on Internet and Information Systems, 18, 7, (2024), 1706-1725. DOI: 10.3837/tiis.2024.07.001.
[BibTeX Style]
@article{tiis:100950, title="MEDU-Net+: a novel improved U-Net based on multi-scale encoder-decoder for medical image segmentation", author="Zhenzhen Yang and Xue Sun and Yongpeng Yang and Xinyi Wu and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2024.07.001}, volume={18}, number={7}, year="2024", month={July}, pages={1706-1725}}