计量学报2026，Vol.47Issue(5)：662-670,9.DOI:10.3969/j.issn.1000-1158.2026.05.04
内窥镜三维重建中的多尺度注意力机制特征匹配
Multi-scale Attentional Feature Matching for Endoscopic 3D Reconstruction
摘要
Abstract
3D reconstruction serves as a key foundation for precise minimally invasive surgery.However,poor texture and insufficient lighting in cavities pose significant challenges to feature matching,a crucial part of 3D reconstruction.a hierarchical structure-enhanced feature matching method is proposed.A C-SuperPoint feature extraction model,integrated with multi-scale attention mechanisms,enhances detection in weak texture areas,increasing the number of extracted feature points by 33.70%on average.Additionally,a P-LightGlue feature matching algorithm based on the transformer architecture performs initial rough matching and refines results through progressive consistency sampling,effectively filtering mismatches and fitting the model.This approach achieves up to 98.72%accuracy and a minimum average matching error of 1.065 1 pixels across multiple datasets.The results confirm that C-SuperPoint can effectively improve feature extraction performance,while P-LightGlue significantly enhances the accuracy and reliability of image processing in minimally invasive surgery.关键词
图像三维重建/内窥镜/特征提取/特征匹配/微创手术/注意力机制/C-SuperPoint/P-LightGlueKey words
3D reconstruction from image/endoscope/feature extraction/feature matching/minimally invasive surgery/attention mechanism/C-SuperPoint/P-LightGlue分类
通用工业技术引用本文复制引用
潘漫凌,陈刚,王洪雁..内窥镜三维重建中的多尺度注意力机制特征匹配[J].计量学报,2026,47(5):662-670,9.基金项目
浙江省自然科学基金联合基金(LBMHY25F030001) （LBMHY25F030001）
浙江省尖兵领雁研发攻关计划(2024C04052) （2024C04052）
