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Complex Background Suppression for Vibro-acoustography Images

机译:振动声像图图像的复杂背景抑制

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摘要

Vibro-acoustography (VA) is an ultrasound-based imaging modality that maps the acoustic response, or acoustic emission, of an object stimulated by two ultrasound waves at slightly different frequencies. VA images typically have a nonzero background intensity which can reduce contrast in images. We present a method that uses the complex representation of the acoustic emission data to estimate and suppress the unwanted background signal. This method utilizes a fast, linear approach to the problem called complex background suppression (CBS) using a square filtering window of size W × W. Images processed with the CBS algorithm have significantly enhanced contrast. Another improvement observed with this method is the ability to better localize objects within the depth direction with respect to the ultrasound transducer. This algorithm was tested on images obtained from scanning a phantom with spherical inclusions, a urethane breast phantom, and in vivo human breast. The results show that image quality is improved through processing with the CBS algorithm by increasing the contrast of features in the images. The contrast in the sphere phantom was increased by factors of 2-12 depending on the sphere. Utilizing the CBS algorithm increased the contrast in breast phantom by factors ranging from 1.1-5.4 for various inclusions. The size of the filtering window, W, affected the contrast achieved between the phantom features such as the spheres or simulated inclusions and the background material. Application of the CBS algorithm also demonstrated that objects could be localized in depth much better as the relationship to image intensity level was directly correlated to objects located at the center of the focal plane in the axial direction. This method has wide applicability for all VA imaging applications.
机译:振动声学成像(VA)是一种基于超声的成像方式,可绘制由两个超声波以略微不同的频率刺激的对象的声响应或声发射。 VA图像通常具有非零的背景强度,这会降低图像的对比度。我们提出了一种使用声发射数据的复杂表示来估计和抑制有害背景信号的方法。这种方法利用快速,线性的方法来解决这个问题,即使用大小为W×W的正方形滤波窗口来处理称为复杂背景抑制(CBS)的问题。使用CBS算法处理的图像具有明显增强的对比度。用这种方法观察到的另一个改进是能够相对于超声换能器更好地定位深度方向内的对象。在通过扫描带有球形内含物的体模,氨基甲酸酯乳腺体模和体内人乳腺获得的图像上测试了该算法。结果表明,通过使用CBS算法进行处理可以提高图像的特征对比度,从而提高图像质量。球体模型中的对比度根据球体而增加了2-12倍。利用CBS算法,对于各种夹杂物,乳房幻像的对比度提高了1.1-5.4。过滤窗口的大小W影响了幻影特征(例如球体或模拟的内含物)与背景材料之间获得的对比度。 CBS算法的应用还表明,由于与图像强度级别的关系与轴向上位于焦平面中心的对象直接相关,因此可以更好地定位对象的深度。该方法对所有VA成像应用具有广泛的适用性。

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