基于高斯混合模型聚类的B超图像颈动脉内膜和中膜厚度检测  

Detection of carotid intima and media thicknesses based on ultrasound B-mode images clustered with Gaussian mixture model

作　　者：戚贵玲 何冰冰 张榆锋[1] 李支尧[2] 莫鸿 程洁 QI Guiling;HE Bingbing;ZHANG Yufeng;LI Zhiyao;MO Hong;CHENG Jie(The Department of Electronic Engineering,School of Information,Yunnan University,Kunming 650091,P.R.China;The Department of Ultrasound,the Third Affiliated Hospital of Kunming Medical College,Kunming 650118,P.R.China)

机构地区：[1]云南大学信息学院电子工程系,昆明650091 [2]昆明医科大学第三附属医院超声科,昆明650118

出　　处：《生物医学工程学杂志》2020年第6期1080-1088,1094,共10页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目(61561049,81771928);云南省高校高原医学电子信息智能检测处理重点实验室资助项目(C176240111001)。

摘　　要：内、中膜厚度是临床上用于评价动脉粥样硬化发展程度的主要指标。目前,基于B超图像测量内、中膜厚度通常由专业医生手动标记内、中膜边界来实现,过程繁琐耗时,人为影响因素多。本文提出了一种基于高斯混合模型(GMM)的聚类灰度阈值法,以检测B超图像中颈动脉内、中膜厚度。首先基于GMM对颈动脉图像灰度聚类,然后用灰度阈值法检测血管壁内、中膜的分界,最后测量二者的厚度。与直接使用灰度阈值法的测量技术相比,颈动脉B超图像的聚类解决了内、中膜灰度边界模糊的问题,从而提高了灰度阈值法的稳定性与检测精度。本研究选取120例健康颈动脉临床试验数据,以两名专家分别手动精细测量4次的内、中膜厚度的均值作为参考值,最终研究结果显示,经GMM聚类后估计的内、中膜厚度的归一化均方根误差(NRMSE)分别为0.1047±0.0762和0.0974±0.0683;与直接进行灰度阈值估计的结果相比,NRMSE的均值分别减小19.6%和22.4%,表明本文所提方法测量精度有所提高;标准差分别减小17.0%和21.7%,表明所提方法稳定性增加。综上,本文方法有助于动脉粥样硬化等血管疾病的早期诊断和病程监测。In clinic,intima and media thickness are the main indicators for evaluating the development of atherosclerosis.At present,these indicators are measured by professional doctors manually marking the boundaries of the inner and media on B-mode images,which is complicated,time-consuming and affected by many artificial factors.A grayscale threshold method based on Gaussian Mixture Model(GMM)clustering is therefore proposed to detect the intima and media thickness in carotid arteries from B-mode images in this paper.Firstly,the B-mode images are clustered based on the GMM,and the boundary between the intima and media of the vessel wall is then detected by the gray threshold method,and finally the thickness of the two is measured.Compared with the measurement technique using the gray threshold method directly,the clustering of B-mode images of carotid artery solves the problem of gray boundary blurring of inner and middle membrane,thereby improving the stability and detection accuracy of the gray threshold method.In the clinical trials of 120 healthy carotid arteries,means of 4 manual measurements obtained by two experts are used as reference values.Experimental results show that the normalized root mean square errors(NRMSEs)of the estimated intima and media thickness after GMM clustering were 0.1047±0.0762 and 0.0974±0.0683,respectively.Compared with the results of the direct gray threshold estimation,means of NRMSEs are reduced by 19.6%and 22.4%,respectively,which indicates that the proposed method has higher measurement accuracy.The standard deviations are reduced by 17.0%and 21.7%,respectively,which indicates that the proposed method has better stability.In summary,this method is helpful for early diagnosis and monitoring of vascular diseases,such as atherosclerosis.

关 键 词：超声图像 颈动脉 内膜和中膜检测 高斯混合模型 聚类 

分 类 号：R445.1[医药卫生—影像医学与核医学] TP391.41[医药卫生—诊断学]