Ismail Dastan, Mustafa Samah
Electrical Engineering, Salahaddin University-Erbil, Kurdistan region, Iraq.
R Soc Open Sci. 2023 Mar 22;10(3):221560. doi: 10.1098/rsos.221560. eCollection 2023 Mar.
This paper presents a new computer-aided microwave monitoring system as a promising, portable and inexpensive tool to detect and localize brain stroke using a bank of a new wavelet-matched filters. The head is exposed to microwave radiation over the band from 1.1 to 3 GHz, and the backscattered signals at a hemi-elliptical array of 16 antenna elements surrounding the head are filtered to analyse the perturbation in the microwave signals from the brain. A novel technique is applied to remove the strong reflection from the air-skull interface as a way to estimate the target response and is compared with different techniques from literature to portray their role in the performance. The study results approve that the intensity and the distribution of wavelet energy and Shannon wavelet entropy in the filtered microwave signal, and the novel tool based on the distance between the wavelet energies at symmetric opposite antennas are promising candidate signatures for computer-aided detection and localization of a stroke.
本文提出了一种新型的计算机辅助微波监测系统,该系统作为一种有前景、便携式且廉价的工具,使用一组新的小波匹配滤波器来检测和定位脑中风。头部暴露于1.1至3 GHz频段的微波辐射下,对围绕头部的16个天线元件的半椭圆形阵列处的后向散射信号进行滤波,以分析来自大脑的微波信号中的扰动。应用了一种新技术来去除空气-颅骨界面的强反射,以此估计目标响应,并与文献中的不同技术进行比较,以描述它们在性能方面的作用。研究结果证实,滤波后的微波信号中的小波能量强度和分布以及香农小波熵,以及基于对称相对天线处小波能量之间距离的新型工具,是用于脑中风计算机辅助检测和定位的有前景的候选特征。