计算机技术与发展2024，Vol.34Issue(5)：52-59,8.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0040
基于形状特征引导的息肉分割网络
Shape Features Guided Network for Polyp Segmentation
摘要
Abstract
Polyp segmentation is a challenging task due to the variable size and shape of polyps and the low contrast between polyps and surrounding mucosa.To improve the segmentation accuracy at polyps with different shapes and tiny-polyps,we propose a shape-guided polyp segmentation network namely SGNet.SGNet mainly includes two contributions:Firstly,we design a detail-sensitive encoder by in-troducing ConvNext,so that the network can extract the details that are crucial to polyp segmentation while extracting global information.Secondly,we design a shape-guided decoder,which can not only effectively adapt to polyps with different shapes,but also extract rich polyp shape features and multi-scale features,thus effectively improving the segmentation accuracy in polyps with different shapes and tiny-polyps.Extensive experiments on three public polyp segmentation datasets(ETIS,Kvasir and CVC-ClinicDB)show that SGNet can accurately segment polyps with different shapes and tiny-polyps,and is superior to the popular polyp segmentation networks in terms of segmentation accuracy in recent years.关键词
深度学习/卷积神经网络/医学图像分割/息肉分割/形状特征Key words
deep learning/convolutional neural network/medical image segmentation/polyp segmentation/shape feature分类
信息技术与安全科学引用本文复制引用
吴英豪,杜晓刚,雷涛,张学军,王营博..基于形状特征引导的息肉分割网络[J].计算机技术与发展,2024,34(5):52-59,8.基金项目
国家自然科学基金(61861024,62271296,62201334) （61861024,62271296,62201334）
