基于DenseNet和混合域注意力的COVID-19低剂量CT图像质量评价  

Image Quality Assessment for Low-dose-CT Images of COVI D-19 Based on DenseNet and Mixed Domain Attention

作　　者：孙荣荣[1] 单飞[2] 叶雯 SUN Rong-rong;SHAN Fei;YE Wen(Shanghai Institute of Measurement and Testing Technology,Shanghai 201203,China;Shanghai Public Health Clinical Center,Shanghai 201508,China)

机构地区：[1]上海市计量测试技术研究院,上海201203 [2]上海市公共卫生临床中心,上海201508

出　　处：《计算机科学》2021年第S02期620-624,共5页Computer Science

基　　金：上海市2021年度“科技创新行动计划”自然科学基金项目(21ZR1479700);上海市公共卫生体系建设三年行动计划(2020-2022年)重点学科建设计划项目核医学与放射卫生学(GWV-10.1-XK10)。

摘　　要：研究COVID-19低剂量CT图像质量评价算法具有重要意义,但基于深度学习的方法随着网络层数的增加会出现梯度消失问题,针对此问题,文中提出了基于混合域注意力的DenseNet算法。DenseNet通过特征重用和网络的紧密连接,在减少参数的同时解决了梯度消失问题;基于人眼的注意力机制,将自下至上和自上而下结构相结合以实现空间注意力;基于人眼视觉具有多通道特性,针对空间域注意力忽略通道域中的信息,研究混合域注意力,并将其引入至DenseNet。分别用斯皮尔曼等级次序相关系数、皮尔逊线性相关系数来衡量客观评价方法的测试结果与主观评价之间的一致性。实验结果表明,所提方法可以较好地模拟人类的视觉特性,更加准确地对COVID-19低剂量CT进行质量评价,评价结果与人类视觉主观感受有较好的一致性。It is important to study the image quality assessment algorithm of low-dose-CT images for COVID-19.However,with the increase of the number of network layers,the gradient will disappear for the method based on deep learning.To solve this problem,this paper proposes DenseNet algorithm based on mixed domain attention.DenseNet solves the problem of gradient vanishing while reducing parameters through feature reuse and tight connection of network.Based on the attention mechanism of human vision,it adopts the combination of bottom-up and top-down structure to realize spatial attention.Based on the multi-channel characteristics of human vision,this paper ignores the information in the channel domain for spatial attention,studies and introduces the mixed domain attention to DenseNet.Spearman rank order correlation coefficient and Pearson linear correlation coefficient are used to measure the consistency between objective assessment method and subjective assessment method.The experimental results show that this method can simulate the human visual characteristics better,and evaluate the quality of low-dose-CT more accurately.The evaluation results are in good agreement with the subjective feelings of human vision.

关 键 词：DenseNet 混合域注意力 COVID-19 低剂量 CT图像 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]