利用声激励和超声图像分析增强超声图像中的针检测

M. Daoud, Ahmad Shtaiyat, R. Alazrai
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引用次数: 2

摘要

超声成像提供了一种低成本、无创的成像方式,通过引导针头指向目标解剖结构,提高针基干预的安全性和成功率。然而,在常规亮度模式(b模式)超声图像中,有限的针头可见性可能会降低实现针轴和针尖精确定位的能力。本文介绍了一种基于计算机的方法来实现超声图像中针的精确检测。在这种方法中,使用声音致动器激发针头以产生通过针头传播的低振幅声波。利用超声成像技术对受激针进行扫描,获得功率多普勒超声图像和b超图像。利用阈值分割和Radon变换分析对功率多普勒图像进行处理,得到针轴的近似估计,并确定包括振动针在内的感兴趣区域(ROI)。此外,通过使用阈值化程序结合自定义Radon变换分析b模式图像中包含针的ROI,实现了针轴的准确估计。最后,通过对b模式图像应用迭代滑动窗口方法来确定针尖的位置,以量化估计的针轴周围的像素强度。利用线性和曲线超声换能器对牛离体肌肉组织标本中插入的8根针的轴和尖端进行检测,评估了该方法的准确性。结果表明,该方法能够检测出插针的轴线和针尖,误差范围分别为0.3°~ 1.0°和0.2 mm ~ 1.0 mm。这些结果表明,在超声引导的针基干预中,应用所提出的方法来增强针的定位是有潜力的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Needle Detection in Ultrasound Images using Acoustic Excitation and Ultrasound Image Analyses
Ultrasound imaging provides a low cost and noninvasive imaging modality to improve the safety and success rate of needle-based interventions by guiding the needle towards the target anatomy. Nevertheless, the limited needle visibility in conventional brightness mode (B-mode) ultrasound images might degrade the capability of achieving accurate localization of the needle axis and tip. In this paper, a computer-based method is introduced to enable accurate needle detection in ultrasound images. In this method, the needle is excited using a voice actuator to generate low-amplitude acoustic waves that propagate through the needle. The excited needle is scanned using ultrasound imaging to acquire a power Doppler ultrasound image and a B-mode ultrasound image. The power Doppler image is processed using thresholding and Radon transform analyses to obtain approximate estimation of the needle axis and identify a region of interest (ROI) that includes the vibrating needle. Moreover, accurate estimation of the needle axis is achieved by analyzing the ROI that includes the needle in the B-mode image using a thresholding procedure combined with a customized Radon transform. Finally, the location of the needle tip is identified by applying an iterative sliding window approach to the B-mode image to quantify the pixel intensities around the estimated needle axis. The accuracy of the proposed method is evaluated by applying the method to detect the axes and tips of eight needles inserted in ex vivo bovine muscle tissue specimens and imaged using linear and curvilinear ultrasound transducers. The results show that the proposed method was able to detect the axes and tips of the inserted needles with error values within the ranges of 0.3° to 1.0° and 0.2 mm to 1.0 mm, respectively. These results suggest the potential of applying the proposed method to enhance the localization of the needle during ultrasound-guided needle-based interventions.
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