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A New Method for Endocardial Boundary Detection Using Genetic Algorithms

机译:基于遗传算法的心内膜边界检测新方法

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摘要

This paper presents a new method for endocardial boundary detection that consists of two major parts. First, the initial endocardial boundary extraction process is designed to reduce the impact of signal dropout in 2-D echocardiograms. Second, the detected endocardial boundary is then refined by the use of genetic algorithms. The proposed refinement step takes the advantages of population-wide searching and energy convergence capability in genetic algorithms. The near-optimal (or optimal) and stable results can be obtained for the detection of cardiac boundary. Experiments on several left ventricular (LV) echocardiograms have been clinically verified for its effectiveness and convenience in handling patient data.
机译:本文提出了一种新的心内膜边界检测方法,该方法包括两个主要部分。首先,最初的心内膜边界提取过程旨在减少二维超声心动图中信号丢失的影响。其次,然后通过使用遗传算法完善检测到的心内膜边界。提出的优化步骤利用了遗传算法中的总体搜索和能量收敛能力。可以为心脏边界的检测获得接近最佳(或最佳)和稳定的结果。临床上已验证了几种左心室(LV)超声心动图的实验,因为其在处理患者数据方面的有效性和便利性。

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