湖南工业大学学报2025，Vol.39Issue(5)：46-51,6.DOI:10.3969/j.issn.1673-9833.2025.05.007
基于RSE-Vnet卷积网络的肺结节分割方法研究
Research on Lung Nodule Segmentation Method Based on RSE-Vnet Convolutional Network
摘要
Abstract
In view of the flaws of under-segmentation and missed detection in fine-grained image segmentation tasks,an improved end-to-end 3D segmentation algorithm,RSE-Vnet,has thus been proposed.With Res2net network incorporated,multi-scale fine-grained features of different nodules can be captured,thus feeding more accurate nodule location information to the network.Meanwhile,residual connections help to avoid network degradation issues,thus establishing a data-driven model for nodules.The attention mechanism can effectively weight important feature channels so as to reduce the interference of background images,with the constructed method solving the problem of under-segmentation and missed detection of multiple types of nodules to some extent.Finally,it can be verified in the LUNA16 dataset,with a 7%increase in model DSC and a 6%increase in detection sensitivity specifically.关键词
计算机辅助诊断/多尺度细粒特征/注意力/Res2net网络/多类型结节Key words
computer-aided diagnosis/multi-scale fine-grained feature/attention/Res2net network/multi-typed nodule分类
计算机与自动化引用本文复制引用
闫永强,秦斌..基于RSE-Vnet卷积网络的肺结节分割方法研究[J].湖南工业大学学报,2025,39(5):46-51,6.基金项目
湖南省自然科学基金资助项目(2023JJ50166) （2023JJ50166）
