超声心动图心肌边缘检测使用优化协议

N. Friedland, D. Adam
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引用次数: 11

摘要

由于超声心动图超声横断面图像质量低且存在高噪声水平,因此确定心室心肌形状是一项困难的任务。在连续二维超声心动图中开发了一种用于腔边界高速检测的自动协议。定义了一维循环马尔可夫随机场,其中场的随机变量是由腔的重心发出的半径。利用模拟退火对由这些随机变量定义的能量函数进行优化。该能量函数由代表最佳边缘检测、腔壁平滑、时间连续性和腔体体积最大化的元素的线性组合组成。优化后的决策规则产生了令人鼓舞的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Echocardiographic myocardial edge detection using an optimization protocol
The definition of the ventricular myocardial shape in echocardiographic ultrasound cross-sectional images is a difficult task due to the low quality of these images and the high noise levels present. An automatic protocol has been developed for high-speed detection of cavity boundaries in sequential 2-D echocardiograms. A 1-D cyclic Markov random field is defined, where the field's random variables are radii emanating from the cavity's center of gravity. An optimization using simulated annealing is performed upon an energy function defined by these random variables. This energy function is composed of a linear combination of elements which represent optimal edge detection, cavity wall smoothness, temporal continuity, and cavity volume maximization. The improved decision rule, which results from this optimization, produced highly encouraging results.<>
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