Segmentation of Left Ventricle of 2D Echocardiographic Image Using Active Contouring

2011 International Conference on Computational Intelligence and Communication Networks Pub Date : 2011-10-07 DOI:10.1109/CICN.2011.146

Shweta Deopujari, Yogita K. Dubey

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Abstract

Cardiovascular diseases are a major health concern worldwide. The left ventricle and in particular the endocardium is a structure of particular interest since it performs the task of pumping oxygenated blood to the entire body. Therefore, segmentation of the left ventricle in echocardiographic images is a task with important diagnostic power. Cardiac function is evaluated quantitatively using echocardiography via the analysis of shape attributes, such as the heart wall thickness or the shape change of the heart wall boundaries. This requires that the complete boundaries of the heart wall be detected from a sequence of two-dimensional ultrasonic images of the heart. The image segmentation process is made difficult since these images are plagued by poor intensity contrast and dropouts caused by the intrinsic limitations of the image formation process. This paper describes a method for obtaining the border of the heart's left ventricle which is useful in the detection of certain heart parameters. The limitation of speckle noise is overcome by smoothening the image using Gaussian filtering.

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基于主动轮廓的二维超声心动图左心室分割

心血管疾病是世界范围内的一个主要健康问题。左心室，特别是心内膜是一个特别有趣的结构，因为它执行向全身泵送含氧血液的任务。因此，超声心动图图像的左心室分割是一项具有重要诊断能力的任务。利用超声心动图通过分析形状属性(如心壁厚度或心壁边界的形状变化)定量评估心功能。这需要从心脏的一系列二维超声图像中检测到心脏壁的完整边界。由于图像形成过程的固有局限性，这些图像受到对比度差和掉差的困扰，使得图像分割过程变得困难。本文描述了一种获取心脏左心室边界的方法，该方法可用于某些心脏参数的检测。利用高斯滤波对图像进行平滑处理，克服了散斑噪声的局限性。

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2011 International Conference on Computational Intelligence and Communication Networks

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