评价超声引导介入技术的新平台

Younsu Kim, Xiaoyu Guo, E. Boctor
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引用次数: 3

摘要

超声引导的针头跟踪系统经常用于外科手术。使用超声波、电磁传感器和光学传感器开发了各种针跟踪技术。为了评估这些新的针跟踪技术,通常需要获取三维体信息来计算从针尖到目标物体的实际距离。由于超声波束厚度的原因,用于比较的图像引导条件往往不一致。由于三维体积是必要的,在手术过程和评估之间通常会有一些时间延迟。这些评估方法通常只能测量最终的针头位置,因为它们会中断手术过程。这项工作的主要贡献是一个实时评估针头跟踪系统的新平台,解决了上述问题。我们开发了新的工具来评估针尖和目标物体之间的精确距离。PZT元件发射单元设计成针引入器形状,可插入针内。我们实时采集了飞行时间和振幅信息。我们提出了两种系统来收集超声信号。我们在超声数据采集系统和高性价比的FPGA板上演示了该平台。鸡胸肉实验的结果表明了跟踪针尖距离时间序列的可行性。我们用plastisol模型进行了验证实验,结果表明,初步数据符合线性回归模型,RMSE小于0.6mm。我们的平台可以使用其他形式的指导应用于更一般的针头跟踪方法。
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New platform for evaluating ultrasound-guided interventional technologies
Ultrasound-guided needle tracking systems are frequently used in surgical procedures. Various needle tracking technologies have been developed using ultrasound, electromagnetic sensors, and optical sensors. To evaluate these new needle tracking technologies, 3D volume information is often acquired to compute the actual distance from the needle tip to the target object. The image-guidance conditions for comparison are often inconsistent due to the ultrasound beam-thickness. Since 3D volumes are necessary, there is often some time delay between the surgical procedure and the evaluation. These evaluation methods will generally only measure the final needle location because they interrupt the surgical procedure. The main contribution of this work is a new platform for evaluating needle tracking systems in real-time, resolving the problems stated above. We developed new tools to evaluate the precise distance between the needle tip and the target object. A PZT element transmitting unit is designed as needle introducer shape so that it can be inserted in the needle. We have collected time of flight and amplitude information in real-time. We propose two systems to collect ultrasound signals. We demonstrate this platform on an ultrasound DAQ system and a cost-effective FPGA board. The results of a chicken breast experiment show the feasibility of tracking a time series of needle tip distances. We performed validation experiments with a plastisol phantom and have shown that the preliminary data fits a linear regression model with a RMSE of less than 0.6mm. Our platform can be applied to more general needle tracking methods using other forms of guidance.
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