Department of Electrical Engg, IIT Roorkee, Roorkee, India.
J Digit Imaging. 2012 Apr;25(2):271-8. doi: 10.1007/s10278-011-9408-8.
This paper presents the boundary detection of atrium and ventricle in echocardiographic images. In case of mitral regurgitation, atrium and ventricle may get dilated. To examine this, doctors draw the boundary manually. Here the aim of this paper is to evolve the automatic boundary detection for carrying out segmentation of echocardiography images. Active contour method is selected for this purpose. There is an enhancement of Chan-Vese paper on active contours without edges. Our algorithm is based on Chan-Vese paper active contours without edges, but it is much faster than Chan-Vese model. Here we have developed a method by which it is possible to detect much faster the echocardiographic boundaries. The method is based on the region information of an image. The region-based force provides a global segmentation with variational flow robust to noise. Implementation is based on level set theory so it easy to deal with topological changes. In this paper, Newton-Raphson method is used which makes possible the fast boundary detection.
本文提出了超声心动图像中心房和心室的边界检测方法。在二尖瓣反流的情况下,心房和心室可能会扩张。为了检查这一点,医生手动绘制边界。本文的目的是开发自动边界检测方法,以实现超声心动图像的分割。为此选择了活动轮廓法。本文对 Chan-Vese 论文中的无边缘活动轮廓进行了增强。我们的算法基于 Chan-Vese 无边缘活动轮廓,但比 Chan-Vese 模型快得多。在这里,我们开发了一种方法,可以更快地检测超声心动图边界。该方法基于图像的区域信息。基于区域的力提供了一种对噪声鲁棒的全局分割,具有变分流。实现基于水平集理论,因此易于处理拓扑变化。本文使用牛顿-拉斐逊方法,实现了快速边界检测。