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Split spectrum processing for enhanced detection of the ultrasonic echo of a moving target in biological tissues

机译:分离频谱处理可增强对生物组织中移动目标超声回波的检测

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This paper describes a biological application for split spectrum processing (SSP). The ultrasonic control of cryosurgery has been reported previously. It was demonstrated chat the echo of the advancing freezing front could be detected during a freeze-thaw cycle. However, the speckle noise can mask the target signal, leading to difficulties in its detection. In this study, a SSP algorithm with a minimisation technique was implemented and compared to linear bandpass filtering. The optimum set of processing parameters for SSP (half-power bandwidth and number of filters, location of the bank of bandpass filters) and for linear filtering (half-power bandwidth and centre frequency) were determined experimentally. Both filtering techniques were successful in locating the target. However, optimum SNR enhancement and axial resolution were achieved with the non-linear minimisation algorithm, which permits rapid and automatic detection of the moving freezing front during cryosurgery.
机译:本文介绍了一种用于拆分频谱处理(SSP)的生物学应用程序。先前已经报道了冷冻手术的超声控制。事实证明,在冻融循环中可以检测到前进的冰冻锋面的回声。但是,斑点噪声会掩盖目标信号,导致检测困难。在这项研究中,实现了一种具有最小化技术的SSP算法,并将其与线性带通滤波进行了比较。实验确定了SSP(半功率带宽和滤波器数量,带通滤波器组的位置)和线性滤波(半功率带宽和中心频率)的最佳处理参数集。两种过滤技术均能成功定位目标。但是,使用非线性最小化算法可以实现最佳的SNR增强和轴向分辨率,从而可以在冷冻手术过程中快速自动检测运动中的冰冻锋面。

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