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
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R78

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北京市自然科学基金(4242014)


Multimodal image fusion of temporomandibular joint area based on dilated residual attention network
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    摘要:

    目的:应用扩张残差注意力网络方法,构建颞下颌关节区多模态融合影像,为提高口腔颞下颌关节多模态融合影像下的综合诊疗能力提供可行性分析。方法:使用扩张残差注意力网络提取磁共振(MR)和锥形束CT(CBCT)的影像特征,使用 “Softmax加权策略”融合特征,再通过影像重建模块将对应的两种模态的影像融合在一起。结果:融合图像可呈现出髁状突皮质骨、髁状突髓质骨、髁状突附丽的肌肉、关节盘4个部位的形态,在峰值信噪比和结构相似度2个评价指标上均表现良好,峰值信噪比范围是10~15,结构相似度范围是0.4~0.6。结论:该方法能做到实时影像融合,最终融合图像可反映出清晰的解剖形态特征,避免多模态影像切换,为口腔专家术前术后临床诊断提供有效的指导。

    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.

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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,(6):781-787

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  • 收稿日期:2024-01-31
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  • 在线发布日期: 2024-06-11
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