Mohamed Moubark Asraf, Nie Luzhen, Mohd Zaman Mohd Hairi, Islam Mohammad Tariqul, Zulkifley Mohd Asyraf, Baharuddin Mohd Hafiz, Alomari Zainab, Freear Steven
Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK.
Diagnostics (Basel). 2023 Mar 18;13(6):1161. doi: 10.3390/diagnostics13061161.
In ultrasound B-mode imaging, the axial resolution (AR) is commonly determined by the duration or bandwidth of an excitation signal. A shorter-duration pulse will produce better resolution compared to a longer one but with compromised penetration depth. Instead of relying on the pulse duration or bandwidth to improve the AR, an alternative method termed filtered multiply and sum (FMAS) has been introduced in our previous work. For spatial-compounding, FMAS uses the autocorrelation technique as used in filtered-delay multiply and sum (FDMAS), instead of conventional averaging. FMAS enables a higher frame rate and less computational complexity than conventional plane-wave compound imaging beamformed with delay and sum (DAS) and FDMAS. Moreover, it can provide an improved contrast ratio and AR. In previous work, no explanation was given on how FMAS was able to improve the AR. Thus, in this work, we discuss in detail the theory behind the proposed FMAS algorithm and how it is able to improve the spatial resolution mainly in the axial direction. Simulations, experimental phantom measurements and in vivo studies were conducted to benchmark the performance of the proposed method. We also demonstrate how the suggested new algorithm may be used in a practical biomedical imaging application. The balloon snake active contour segmentation technique was applied to the ultrasound B-mode image of a common carotid artery produced with FMAS. The suggested method is capable of reducing the number of iterations for the snake to settle on the region-of-interest contour, accelerating the segmentation process.
在超声B模式成像中,轴向分辨率(AR)通常由激励信号的持续时间或带宽决定。与较长持续时间的脉冲相比,较短持续时间的脉冲将产生更好的分辨率,但穿透深度会降低。在我们之前的工作中,引入了一种称为滤波相乘求和(FMAS)的替代方法,而不是依靠脉冲持续时间或带宽来提高轴向分辨率。对于空间复合,FMAS使用滤波延迟相乘求和(FDMAS)中使用的自相关技术,而不是传统的平均方法。与使用延迟求和(DAS)和FDMAS进行波束形成的传统平面波复合成像相比,FMAS能够实现更高的帧率和更低的计算复杂度。此外,它还可以提供更高的对比度和轴向分辨率。在之前的工作中,没有对FMAS如何能够提高轴向分辨率做出解释。因此,在这项工作中,我们详细讨论了所提出的FMAS算法背后的理论,以及它如何主要在轴向方向上提高空间分辨率。进行了模拟、实验体模测量和体内研究,以对所提出方法的性能进行基准测试。我们还展示了所建议的新算法如何应用于实际的生物医学成像应用中。将气球蛇主动轮廓分割技术应用于用FMAS生成的颈总动脉超声B模式图像。所建议的方法能够减少蛇形算法在感兴趣区域轮廓上收敛所需的迭代次数,从而加速分割过程。