A two-dimensional CVIB imaging system with a speckle tracking algorithm

被引:2
|
作者
Bai, Jing [1 ]
Liu, Ke [1 ]
Jiang, Yong [1 ]
Ying, Kui [1 ]
Zhang, Pengfei [2 ]
Shao, Jinhua [1 ]
机构
[1] Tsinghua Univ, Dept Biomed Engn, Beijing 100084, Peoples R China
[2] Shandong Univ, Dept Cardiol, Qilu Hosp, Jinan 250012, Peoples R China
基金
高等学校博士学科点专项科研基金;
关键词
myocardial ischemia; cyclic variation in integrated backscatter; integrated backscatter; speckle tracking; ultrasound;
D O I
10.1016/j.ultras.2008.01.010
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Quantitative ultrasound tissue characterization based on integrated backscatter (IB) has shown great potential in detecting myocardial ischemia. The magnitude of the cyclic variation in IB (CVIB) has been considered one promising parameter in assessing regional myocardial contractile performance. This lab has previously developed a novel ultrasonic fusion imaging method based on CVIB. However, the major problem for clinical applications of this technique is that the myocardial tissue could not be tracked effectively without cardiologist's intervention. This paper introduced a speckle tracking method into the CVIB-weighted imaging system, called speckle tracking algorithm with adaptive window size (STAWAWS), to track myocardial tissue particle automatically. This method provides a way to obtain the particle's positions frame by frame in a series of B-mode images. Then using the RF signals according to the particle's positions the IB curve can be calculated to produce CVIB value. The method was applied on the experimental and clinical data cases's analysis. The results of dog's data processing showed that this method could eliminate the misunderstanding of myocardial ischemia especially near the endocardium. The results of clinical data suggested that this method had clinical significance in detecting ischemic myocardium. Though the CVIB-weighted images obtained by the use of this auto-tracking method can improve the accuracy of detecting myocardial ischemia, it is not real-time analysis and the clinical data cases are not sufficient. Further clinical validation is still needed in the future' work. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:394 / 402
页数:9
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