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Coronary Plaque Boundary Detection in Intravascular Ultrasound Image by Using Hybrid Modified Level Set Method and Fuzzy Inference

机译:使用混合改性水平集法和模糊推断,冠心脉超声图像冠状动脉斑块边界检测

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This paper describes a boundary detection of coronary plaque by a hybrid of a modified level set method and a fuzzy inference. The standard level set method to detect an image boundary commonly uses an image gradient for calculating a speed function. But the speed function of the level set cannot work well within an intravascular ultrasound (IVUS) image, which is the target of this paper. Therefore, we proposed a method for coronary boundary detection in IVUS image by using a modified level set method. In that method, the image gradient in the speed function is substituted by the weighted image separability. However, some regions of the IVUS image often becomes shadowed and then contains no texture information, due to the presence of the guide wire. Thus the modified level set method fails to detect the plaque boundary in those regions. To solve this problem, we further propose in this paper, a hybrid of the modified level set method and the T-S fuzzy model. The present method has been more successful in the accuracy of plaque boundary detection.
机译:本文介绍了改进水平集法的混合动力和模糊推理的冠状动脉斑块的边界检测。检测图像边界的标准级别设置方法通常使用图像梯度来计算速度函数。但水平集的速度函数不能很好地适用于血管内超声(IVUS)图像,这是本文的目标。因此,我们通过使用修改的级别设置方法提出了一种在IVUS图像中的冠状动脉边界检测方法。在该方法中,速度函数中的图像梯度由加权图像可分离性代替。然而,由于导丝的存在,IVUS图像的一些区域经常被遮蔽,然后不包含纹理信息。因此,修改的水平集合方法无法检测这些区域中的斑块边界。为了解决这个问题,我们进一步提出了本文的修改水平集方法和T-S模糊模型的混合。本方法在斑块边界检测的准确性方面更加成功。

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