基于PM-UNet的腹部肝脏分割网络
王智信 （ 北方工业大学 信息学院 ）
https://doi.org/10.37155/2717-5669-0601-19Abstract
传统卷积神经网络在捕捉全局上下文信息和多尺度特征提取上存在局限，容易忽视重要特征。为此，提 出一种结合并行注意力和多尺度卷积交叉融合的网络。并行注意力机制有效捕捉全局信息和通道关系，抑制无关特 征；多尺度卷积模块通过不同感受野融合特征，增强表达能力。实验结果表明，该方法在3DIRCADb数据集上显著优 于现有分割网络，分割结果更接近真实值。
Keywords
深度学习；肝脏分割Full Text
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Copyright © 2025 王智信
Publishing time:2025-01-31
This work is licensed under a Creative Commons Attribution 4.0 International License
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