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Wavelet-based edge detection in ultrasound images.

机译:超声图像中基于小波的边缘检测。

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摘要

We introduce a new wavelet-based method for edge detection in ultrasound (US) images. Each beam that is analyzed is first transformed into the wavelet domain using the continuous wavelet transform (CWT). Because the CWT preserves both scale and time information, it is possible to separate the signal into a number of scales. The edge is localized by first determining the scale at which the power spectrum, based on the wavelet transform, has its maximum value. Next, at this scale we find the position of the peak for the squared CWT. This method does not depend on any threshold, after the range of scales have been determined. We suggest a range of scales for US images in general. Sample edge detections are demonstrated in US images of straight and jagged edges of simple structures submerged in water bath, and of an abdominal aorta aneurysm phantom.
机译:我们介绍了一种新的基于小波的超声(US)图像边缘检测方法。首先,使用连续小波变换(CWT)将被分析的每个波束转换到小波域。由于CWT保留了比例尺和时间信息,因此可以将信号分成多个比例尺。通过首先基于小波变换确定功率谱具有最大值的比例来对边缘进行定位。接下来,在此比例下,我们找到平方CWT的峰位置。确定标度范围后,此方法不依赖任何阈值。一般而言,我们建议对美国图像使用不同的比例尺。样本边缘检测在浸没在水浴中的简单结构的笔直和锯齿状边缘以及腹部主动脉瘤幻像的美国图像中得到了证明。

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