可持续发展论坛

基于上下文感知的轻量化医学图像分割方法

杨 晋权

湖南工业大学

胡 永祥

湖南工业大学

DOI: https://doi.org/10.59429/kcxfzlt.v3i1.14094

Keywords: 医学图像分割；注意力机制；轻量化

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Abstract

针对临床实时分析、边缘设备部署以及资源受限平台中，提出了一种轻量化医学图像分割模型NeoMorphUNet。该模型在保持 U 型结构的基础上，从特征提取、跳跃连接增强和跨层融合三个关键环节进行轻量化设计。具体而言，通过构建 CHC Block 提升多尺度上下文信息和方向结构特征的提取能力；引入 SAG Block 增强浅层特征的目标响应能力，并设计 GAF Block 实现深浅层特征的高效融合，从而在降低模型复杂度的同时保持较好的分割性能。在两个公开数据集上的实验结果表明，该模型在显著减少参数量与计算量的情况下仍具备较强竞争力。

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