基于分段反投影张量退化特征编码的牙科锥形束计算机断层扫描运动伪影校正  

A segmented backprojection tensor degradation feature encoding model for motion artifacts correction in dental cone beam computed tomography

作　　者：曾智雄 王永波 林宗悦 边兆英[1,3] 马建华[1] ZENG Zhixiong;WANG Yongbo;LIN Zongyue;BIAN Zhaoying;MA Jianhua(School of Biomedical Engineering,Southern Medical University,Guangzhou 510515,China;School of Life Science and Technology,Xi'an Jiaotong University,Xi'an 710049,China;Guangdong Provincial Key Laboratory of Medical Image Processing,Southern Medical University,Guangzhou 510515,China)

机构地区：[1]南方医科大学生物医学工程学院,广东广州510515 [2]西安交通大学生命科学与技术学院,陕西西安710049 [3]南方医科大学广东省医学图像处理重点实验室,广东广州510515

出　　处：《南方医科大学学报》2025年第2期422-436,共15页Journal of Southern Medical University

基　　金：国家自然科学基金(U21A6005);广州市科技计划项目(202206010148)。

摘　　要：目的为了去除患者在牙科锥形束计算机断层扫描(CBCT)扫描过程中发生躯体运动导致的伪影,提升重建图像质量,提出一种基于分段反投影张量退化特征编码的运动伪影校正模型(SBP-MAC)。方法该模型由一个生成器和一个退化编码器构成。将分段有限角度重建的子图像堆叠成张量并作为模型输入;用退化编码器提取张量中空间变化的运动信息,自适应调制生成器的各级跳跃连接特征,从而指导模型校正不同运动波形导致的伪影;最后设计伪影一致性损失来简化生成器的学习任务。结果该模型能有效地去除运动伪影,提升重建图像质量。在仿真数据上的峰值信噪比提升了8.28%,结构相似度提升了2.29%,均方根误差降低了23.84%;在真实数据上的专家评分最高4.4221(5分制),与所有对比方法之间的评分差异具有统计学意义(P<0.05)。结论本文提出的SBP-MAC模型能够有效提取张量中空间变化的运动信息,实现从张量域到图像域的自适应伪影校正,提升牙科CBCT图像质量。Objective We propose a segmented backprojection tensor degradation feature encoding(SBP-MAC)model for motion artifact correction in dental cone beam computed tomography(CBCT)to improve the quality of the reconstructed images.Methods The proposed motion artifact correction model consists of a generator and a degradation encoder.The segmented limited-angle reconstructed sub-images are stacked into the tensors and used as the model input.A degradation encoder is used to extract spatially varying motion information in the tensor,and the generator's skip connection features are adaptively modulated to guide the model for correcting artifacts caused by different motion waveforms.The artifact consistency loss function was designed to simplify the learning task of the generator.Results The proposed model could effectively remove motion artifacts and improve the quality of the reconstructed images.For simulated data,the proposed model increased the peak signal-to-noise ratio by 8.28%,increased the structural similarity index measurement by 2.29%,and decreased the root mean square error by 23.84%.For real clinical data,the proposed model achieved the highest expert score of 4.4221(against a 5-point scale),which was significantly higher than those of all the other comparison methods.Conclusion The SBP-MAC model can effectively extract spatially varying motion information in the tensors and achieve adaptive artifact correction from the tensor domain to the image domain to improve the quality of reconstructed dental CBCT images.

关 键 词：运动伪影校正 牙科锥形束计算机断层扫描 分段反投影张量 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]