SEU2-Net: multi-scale U2-Net with SE attention mechanism for liver occupying lesion CT image segmentation.
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ABSTRACT:
SUBMITTER: Liu L
PROVIDER: S-EPMC10909188 | biostudies-literature | 2024
REPOSITORIES: biostudies-literature
Publications
SEU<sup>2</sup>-Net: multi-scale U<sup>2</sup>-Net with SE attention mechanism for liver occupying lesion CT image segmentation.
Liu Lizhuang L Wu Kun K Wang Ke K Han Zhenqi Z Qiu Jianxing J Zhan Qiao Q Wu Tian T Xu Jinghang J Zeng Zheng Z
PeerJ. Computer science 20240125
Liver occupying lesions can profoundly impact an individual's health and well-being. To assist physicians in the diagnosis and treatment of abnormal areas in the liver, we propose a novel network named SEU<sup>2</sup>-Net by introducing the channel attention mechanism into U<sup>2</sup>-Net for accurate and automatic liver occupying lesion segmentation. We design the Residual U-block with Squeeze-and-Excitation (SE-RSU), which is to add the Squeeze-and-Excitation (SE) attention mechanism at the ...[more]
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