南京医科大学学报（自然科学版）2024，Vol.44Issue(6)：781-787,7.DOI:10.7655/NYDXBNSN
基于扩张残差注意力网络的颞下颌关节区多模态影像融合
Multimodal image fusion of temporomandibular joint area based on dilated residual attention network
摘要
Abstract
Objective:To explore the feasibility of constructing multimodal fused images of the temporomandibular joint area using the dilated residual attention network method,and to provide a feasibility analysis for improving the comprehensive diagnostic and therapeutic capabilities under multimodal fusion imaging of the oral temporomandibular joint.Methods:The dilated residual attention network was used to extract image features of MR and CBCT,and a"Softmax weighting strategy"to fuse the features.Subsequently,the corresponding images of the two modalities were fused together through an image reconstruction module.Results:The fused images could present the morphology of condylar cortical bone,condylar medullary bone,condylar attached muscles and articular disc.The fused images performed well in terms of peak signal-to-noise ratio and structural similarity index,with peak signal-to-noise ratio ranging from 10 to 15 and structural similarity index ranging from 0.4 to 0.6.Conclusion:This method can achieve real-time image fusion,the final fused image can reflect clear anatomical morphological features,thus avoiding the need for switching between multimodal images and providing effective guidance for dental experts in preoperative and postoperative clinical diagnosis.关键词
影像融合/颞下颌关节/CBCT/MRKey words
image fusion/temporomandibular joint/CBCT/MR分类
医药卫生引用本文复制引用
茆晓源,陈岩,何晓彤,孙强,张朝晖..基于扩张残差注意力网络的颞下颌关节区多模态影像融合[J].南京医科大学学报（自然科学版）,2024,44(6):781-787,7.基金项目
北京市自然科学基金(4242014) （4242014）
