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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Point spread functions and deconvolution of ultrasonic images
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Point spread functions and deconvolution of ultrasonic images

机译：点扩散函数和超声图像反卷积

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This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.
机译：本文研究了通过点扩展函数（PSF）的去卷积方法恢复超声脉冲回波C扫描图像的方法。将线性系统理论（LST）的反卷积概念与成像过程的波动方程公式联系起来，并得出平面换能器PSF的解析公式。对于该解析表达式，提出了用于评估PSF的不同数值和解析近似方案。通过将模拟图像与测得的C扫描图像进行比较，我们证明LST的假设与我们针对PSF的公式相结合是脉冲回波成像过程的良好模型。为了从C扫描图像中重建对象，我们比较了不同的反卷积方案：Wiener滤波器，ForWaRD算法和Richardson-Lucy算法。使用总变化正则化的Richardson-Lucy算法可获得最佳结果。对于大于或等于近场距离两倍的距离，我们的实验表明，可以使用基于远场近似的简单封闭解析项代替数值计算的PSF。

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