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Deconvolution of vibroacoustic images using a simulation model based on a three dimensional point spread function

机译:使用基于三维点扩散函数的模拟模型对振动声图像进行反卷积

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Vibro-acoustography (VA) is a medical imaging method based on the difference-frequency generation produced by the mixture of two focused ultrasound beams. VA has been applied to different problems in medical imaging such as imaging bones, microcalcifications in the breast, mass lesions, and calcified arteries. The obtained images may have a resolution of 0.7-0.8 mm. Current VA systems based on confocal or linear array transducers generate C-scan images at the beam focal plane. Images on the axial plane are also possible, however the system resolution along depth worsens when compared to the lateral one. Typical axial resolution is about 1.0 cm. Furthermore, the elevation resolution of linear array systems is larger than that in lateral direction. This asymmetry degrades C-scan images obtained using linear arrays. The purpose of this article is to study VA image restoration based on a 3D point spread function (PSF) using classical deconvolution algorithms: Wiener, constrained least-squares (CLSs), and geometric mean filters. To assess the filters' performance on the restored images, we use an image quality index that accounts for correlation loss, luminance and contrast distortion. Results for simulated VA images show that the quality index achieved with the Wiener filter is 0.9 (when the index is 1.0 this indicates perfect restoration). This filter yielded the best result in comparison with the other ones. Moreover, the deconvolution algorithms were applied to an experimental VA image of a phantom composed of three stretched 0.5 mm wires. Experiments were performed using transducer driven at two frequencies, 3075 kHz and 3125 kHz, which resulted in the difference-frequency of 50 kHz. Restorations with the theoretical line spread function (LSF) did not recover sufficient information to identify the wires in the images. However, using an estimated LSF the obtained results displayed enough information to spot the wires in the images. It is demonstrated that the phase of the theoretical and the experimental PSFs are dissimilar. This fact prevents VA image restoration with the current theoretical PSF. This study is a preliminary step towards understanding the restoration of VA images through the application of deconvolution filters.
机译:振动声学成像(VA)是一种医学成像方法,基于两种聚焦超声束的混合所产生的差频产生。 VA已应用于医学成像中的其他问题,例如骨骼成像,乳房微钙化,肿块病变和钙化动脉。所获得的图像可以具有0.7-0.8mm的分辨率。基于共焦或线性阵列换能器的当前VA系统在光束焦平面处生成C扫描图像。轴向平面上的图像也是可能的,但是与横向图像相比,沿深度的系统分辨率会降低。典型的轴向分辨率约为1.0厘米。此外,线性阵列系统的仰角分辨率大于横向分辨率。这种不对称会使使用线性阵列获得的C扫描图像降级。本文的目的是使用经典的反卷积算法:Wiener,约束最小二乘(CLS)和几何均值滤波器,研究基于3D点扩展函数(PSF)的VA图像恢复。为了评估滤镜在还原图像上的性能,我们使用图像质量指数来说明相关损失,亮度和对比度失真。模拟VA图像的结果表明,使用维纳滤镜获得的质量指数为0.9(当指数为1.0时,这表示完美的恢复)。与其他滤波器相比,此滤波器产生了最佳结果。此外,将反卷积算法应用于由三根拉伸的0.5毫米导线组成的模型的实验VA图像。使用以两个频率3075 kHz和3125 kHz驱动的换能器进行实验,结果得到了50 kHz的差频。使用理论线散布函数(LSF)进行的还原无法恢复足够的信息来识别图像中的导线。但是,使用估计的LSF,获得的结果显示了足够的信息以在图像中发现导线。结果表明,理论和实验PSF的相位是不同的。这一事实阻止了使用当前理论PSF进行VA图像恢复。这项研究是通过使用反卷积滤波器了解VA图像恢复的初步步骤。

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