|本期目录/Table of Contents|

[1]李锵,张琦珺,关欣,等.基于改进模糊C均值算法的颈动脉超声图像分割[J].天津大学学报(自然科学版),2018,(01):95-102.[doi:10.11784/tdxbz201612044]
 Li Qiang,Zhang Qijun,Guan Xin,et al.Segmentation of Carotid Intima Media in Ultrasound Images Using Improved Fuzzy C Means Algorithm[J].Journal of Tianjin University,2018,(01):95-102.[doi:10.11784/tdxbz201612044]
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基于改进模糊C均值算法的颈动脉超声图像分割()
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《天津大学学报(自然科学版)》[ISSN:0493-2137/CN:12-1127/N]

卷:
期数:
2018年01
页码:
95-102
栏目:
出版日期:
2018-01-08

文章信息/Info

Title:
Segmentation of Carotid Intima Media in Ultrasound Images Using Improved Fuzzy C Means Algorithm
文章编号:
0493-2137(2018)01-0095-08
作者:
李锵 张琦珺 关欣 滕建辅
天津大学微电子学院,天津 300072
Author(s):
Li Qiang Zhang Qijun Guan Xin Teng Jianfu
School of Microelectronics, Tianjin University, Tianjin 300072, China
关键词:
超声图像分割 内中膜厚度测量 模糊C均值 隐马尔可夫随机场模型 感兴趣区域
Keywords:
ultrasound image segmentation intima-media thickness(IMT)measurement fuzzy C means(FCM) hidden Markov random field(HMRF)model region of interest(ROI)
分类号:
TP391.7;R445.1
DOI:
10.11784/tdxbz201612044
文献标志码:
A
摘要:
颈动脉的内中膜厚度(IMT)是预测心血管疾病(CVDs)病发程度的重要指标.本文研究并提出一种自动、高效的计算机辅助IMT测量算法, 该算法依据先验知识自动提取感兴趣区域(ROI), 并采用基于隐马尔可夫随机场(HMRF)模型改进的模糊C均值(FCM)算法分割图像, 实现IMT的自动测量.实验结果表明, 所提算法对超声图像噪声的鲁棒性较强, IMT自动测量结果与真实值(GT)有很高的一致性:两个数据集合的相关系数为98.52%, 平均绝对误差为.
Abstract:
Common carotid artery intima-media thickness(IMT),which is considered as an important indicator of the development of cardiovascular diseases(CVDs),is usually measured on ultrasound images. This paper proposed an automatic and efficient computer-aided IMT measurement system. With the proposed method,region of interest(ROI)is extracted automatically based on prior knowledge,and then improved fuzzy C means(FCM)based on hidden Markov random field(HMRF)were applied to segment ROI and to detect the boundary of intima-media for IMT measurement. Experimental results show that the proposed method has strong robustness against ultrasound artifacts,and achieves similar clinical parameters to the ground truth(GT). The correlation coefficient between the two databases reaches 98.52% ,and the mean of the absolute error between them is .

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2016-12-19; 修回日期: 2017-03-08.
作者简介: 李锵(1974—), 男, 博士, 教授, liqiang@tju.edu.cn.
通讯作者: 张琦珺, zqjyx@tju.edu.cn.
基金项目: 国家自然科学基金资助项目(61471263).
Supported by the National Natural Science Foundation of China(No.,61471263).
更新日期/Last Update: 2018-01-10