MSAA-Net: a multi-scale attention-aware U-Net is used to segment the liver-Reference-Cited by-同舟云学术

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MSAA-Net: a multi-scale attention-aware U-Net is used to segment the liver

Published:2022-08-10 Issue:4 Volume:17 Page:1001-1009
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Zhang Lijuan,Liu Jiajun,Li Dongming,Liu Jinyuan,Liu Xiangkun

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-022-02305-0.pdf

Reference34 articles.

1. Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R.L., Torre, L.A., Jemal, A.: Global cancer statistics 2018: globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68(6), 394–424 (2018)

2. Litjens, G., Kooi, T., Bejnordi, B.E., Setio, A.A.A., Ciompi, F., Ghafoorian, M., Van Der Laak, J.A., Van Ginneken, B., Sánchez, C.I.: A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60–88 (2017)

3. Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp. 234–241 (2015). Springer

4. Çiçek, Ö., Abdulkadir, A., Lienkamp, S.S., Brox, T., Ronneberger, O.: 3d u-net: learning dense volumetric segmentation from sparse annotation. In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp. 424–432 (2016). Springer

5. Fang, X., Yan, P.: Multi-organ segmentation over partially labeled datasets with multi-scale feature abstraction. IEEE Trans. Med. Imaging 39(11), 3619–3629 (2020)

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1. CT image liver segmentation based on improved Deeplabv3+;2023 2nd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC);2023-08-11

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