[1]刘子玲,刘巧红,叶熊,等.融合块匹配和插值法的膈肌应变估计及分析[J].中国医学物理学杂志,2022,39(11):1360-1368.[doi:DOI:10.3969/j.issn.1005-202X.2022.11.008]
 LIU Ziling,LIU Qiaohong,YE Xiong,et al.Diaphragm strain estimation and analysis using block matching algorithm and interpolation method[J].Chinese Journal of Medical Physics,2022,39(11):1360-1368.[doi:DOI:10.3969/j.issn.1005-202X.2022.11.008]
点击复制

融合块匹配和插值法的膈肌应变估计及分析()
分享到:

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
39卷
期数:
2022年第11期
页码:
1360-1368
栏目:
医学影像物理
出版日期:
2022-11-25

文章信息/Info

Title:
Diaphragm strain estimation and analysis using block matching algorithm and interpolation method
文章编号:
1005-202X(2022)11-1360-09
作者:
刘子玲1刘巧红2叶熊3撖子奇1
1.上海理工大学健康科学与工程学院, 上海 200093; 2.上海健康医学院医疗器械学院, 上海 201318; 3.上海健康医学院临床医学院, 上海 201318
Author(s):
LIU Ziling1 LIU Qiaohong2 YE Xiong3 HAN Ziqi1
1. School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China 2. School of Medical Instruments, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China 3. School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
关键词:
膈肌超声图像块匹配算法插值法应变估计
Keywords:
Keywords: diaphragm ultrasound image block matching algorithm interpolation method strain estimation
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2022.11.008
文献标志码:
A
摘要:
为了准确评估膈肌收缩功能,提出一种融合块匹配法和插值法的膈肌运动位移和应变估计方法。首先利用基于归一化互相关的块匹配法结合膈肌生理约束特性估计出膈肌感兴趣区域的互相关函数,对膈肌运动的整数位移进行估计;然后利用9点抛物线插值算法对互相关函数进行插值处理,进一步计算膈肌感兴趣区域二维亚像素位移;接下来根据估计出的位移计算应变;最后利用反追踪的思想选取最佳窗口的大小,以降低位移追踪误差。按照上述方法,分别针对吸气相超声膈肌全序列图像以及含吸气开始和吸气结束的首尾两张膈肌图像进行追踪,观察不同大小感兴趣区域窗口设置对膈肌运动位移和应变估计的影响。实验结果表明块匹配算法的窗口大小选择中,5×10和10×15窗口存在匹配错误,15×20、20×25、25×30、30×35窗口追踪得到的水平位移和竖直位移均无显著差异,而固定窗口大小为25×30最佳;选择使用全序列图像和首尾两张图像对膈肌全局应变计算不存在显著差异。
Abstract:
Abstract: A method combining block matching algorithm with interpolation method is proposed to estimate diaphragm motion displacement and strain for evaluating diaphragm contractility accurately. According to the physiological restraint characteristics of the diaphragm, block matching algorithm based on normalized cross-correlation is used to estimate the cross-correlation function of the region of interest (ROI) of the diaphragm, thereby estimating the integer displacement of the diaphragm motion. Then, a 9-point parabolic interpolation algorithm is used to interpolate the cross-correlation function for obtaining the two-dimensional subpixel displacement of the diaphragm ROI, and the strain is calculated according to the estimated displacement. Finally, the optimal window size is confirmed using the idea of reverse tracking for reducing the displacement tracking error. The whole sequence images of the diaphragm in the inspiratory phase and the fore and aft images of the diaphragm obtained at the beginning and end of inspiratory phase are tracked by the proposed method to analyze the effects of different ROI window sizes on the estimations of diaphragm motion displacement and strain. Experimental results show that there are matching errors in 5×10 and 10×15 windows. The differences in horizontal and vertical displacements tracked by windows of 15×20, 20×25, 25×30 and 30×35 are trivial, and the optimal window size is 25×30. There is no significant difference in diaphragm global strain calculated in whole sequence images or fore and aft images.

相似文献/References:

[1]张绿川,杨艳.基于稀疏表示超像素分类的肿瘤超声图像分割算法[J].中国医学物理学杂志,2015,32(06):855.[doi:doi:10.3969/j.issn.1005-202X.2015.06.020]
 [J].Chinese Journal of Medical Physics,2015,32(11):855.[doi:doi:10.3969/j.issn.1005-202X.2015.06.020]
[2]刘一学,李锵,关欣,等.基于支持向量机的颈动脉超声图像内中膜厚度测量[J].中国医学物理学杂志,2016,33(5):451.[doi:10.3969/j.issn.1005-202X.2016.05.005]
 [J].Chinese Journal of Medical Physics,2016,33(11):451.[doi:10.3969/j.issn.1005-202X.2016.05.005]
[3]吴金风,张东. 高强度聚焦超声图像斑点解相关特性分析[J].中国医学物理学杂志,2017,34(6):590.[doi:DOI:10.3969/j.issn.1005-202X.2017.06.010]
 [J].Chinese Journal of Medical Physics,2017,34(11):590.[doi:DOI:10.3969/j.issn.1005-202X.2017.06.010]
[4]惠钊,黄慧明.基于比率距离的自适应超声图像去噪方法[J].中国医学物理学杂志,2020,37(2):174.[doi:DOI:10.3969/j.issn.1005-202X.2020.02.008]
 HUI Zhao,HUANG Huiming.Adaptive ultrasound image denoising method based on ratio distance[J].Chinese Journal of Medical Physics,2020,37(11):174.[doi:DOI:10.3969/j.issn.1005-202X.2020.02.008]
[5]崔梦瑶,应潇挺,赵兴群,等.肾脏射频消融中超声图像特征参数与温度关系的研究[J].中国医学物理学杂志,2020,37(9):1164.[doi:10.3969/j.issn.1005-202X.2020.09.016]
 CUI Mengyao,YING Xiaoting,ZHAO Xingqun,et al.Correlation between renal ultrasound image features and temperature during radiofrequencyablation[J].Chinese Journal of Medical Physics,2020,37(11):1164.[doi:10.3969/j.issn.1005-202X.2020.09.016]
[6]陈泽钰,葛云,陈颖,等.基于双目红外相机定位的自由式三维超声图像重建系统[J].中国医学物理学杂志,2021,38(8):960.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.008]
 CHEN Zeyu,GE Yun,CHEN Ying,et al.Freehand three-dimensional ultrasound image reconstruction system based on binocular infrared camera positioning[J].Chinese Journal of Medical Physics,2021,38(11):960.[doi:DOI:10.3969/j.issn.1005-202X.2021.08.008]
[7]贺桢,石蕴玉,刘翔,等.基于卷积神经网络检测颈动脉斑块[J].中国医学物理学杂志,2022,39(1):122.[doi:DOI:10.3969/j.issn.1005-202X.2022.01.020]
 HE Zhen,SHI Yunyu,LIU Xiang,et al.Detection of carotid plaques based on convolutional neural network[J].Chinese Journal of Medical Physics,2022,39(11):122.[doi:DOI:10.3969/j.issn.1005-202X.2022.01.020]
[8]孙国栋,石蕴玉,刘翔,等.超声图像血管分割的研究进展[J].中国医学物理学杂志,2022,39(4):453.[doi:DOI:10.3969/j.issn.1005-202X.2022.04.011]
 SUN Guodong,SHI Yunyu,LIU Xiang,et al.Advances in blood vessel segmentation in ultrasound image[J].Chinese Journal of Medical Physics,2022,39(11):453.[doi:DOI:10.3969/j.issn.1005-202X.2022.04.011]

备注/Memo

备注/Memo:
【收稿日期】2022-06-11 【基金项目】国家自然科学基金(61801288) 【作者简介】刘子玲,硕士,研究方向:医学图像处理技术,E-mail: 824557214@qq.com 【通信作者】刘巧红,博士,副教授,研究方向:医学图像处理技术、医疗影像大数据技术,E-mail: hqllqh@163.com
更新日期/Last Update: 2022-11-25