Arterial Distension Monitoring Scheme Using FPGA-Based Inference Machine in Ultrasound Scanner Circuit System

Young-Chan Lee;Doo-Hyeon Ko;Min-Hyeong Son;Se-Hwan Yang;Ji-Yong Um
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Abstract

This paper presents an arterial distension monitoring scheme using a field-programmable gate array (FPGA)-based inference machine in an ultrasound scanner circuit system. An arterial distension monitoring requires a precise positioning of an ultrasound probe on an artery as a prerequisite. The proposed arterial distension monitoring scheme is based on a finite state machine that incorporates sequential support vector machines (SVMs) to assist in both coarse and fine adjustments of probe position. The SVMs sequentially perform recognitions of ultrasonic A-mode echo pattern for a human carotid artery. By employing sequential SVMs in combination with convolution and average pooling, the number of features for the inference machine is significantly reduced, resulting in less utilization of hardware resources in FPGA. The proposed arterial distension monitoring scheme was implemented in an FPGA (Artix7) with a resource utilization percentage less than 9.3%. To demonstrate the proposed scheme, we implemented a customized ultrasound scanner consisting of a single-element transducer, an FPGA, and analog interface circuits with discrete chips. In measurements, we set virtual coordinates on a human neck for 9 human subjects. The achieved accuracy of probe positioning inference is 88%, and the Pearson coefficient (r) of arterial distension estimation is 0.838.
在超声扫描仪电路系统中使用基于 FPGA 的推理机的动脉扩张监测方案。
本文介绍了在超声扫描仪电路系统中使用基于现场可编程门阵列(FPGA)推理机的动脉扩张监测方案。动脉扩张监测需要以超声探头在动脉上的精确定位为前提。所提出的动脉扩张监测方案以有限状态机为基础,其中包含顺序支持向量机 (SVM),以帮助粗调和微调探头位置。SVM 依次识别人体颈动脉的超声 A 模回波模式。通过将顺序 SVM 与卷积和平均池相结合,推理机的特征数量大大减少,从而降低了 FPGA 硬件资源的利用率。在 FPGA(Artix7)中实现了拟议的动脉扩张监测方案,资源利用率低于 9.3%。为了演示所提出的方案,我们实现了一个定制的超声扫描仪,该扫描仪由一个单元素传感器、一个 FPGA 和带有分立芯片的模拟接口电路组成。在测量中,我们为 9 名受试者设置了人体颈部的虚拟坐标。探头定位推断的准确率达到 88%,动脉扩张估计的皮尔逊系数 (r) 为 0.838。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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