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基于微波聚焦天线的肺部感染检测OA

Detection of pulmonary infection based on focused microwave antenna

中文摘要英文摘要

在推导平面场源在多层人体组织中磁场分布的基础上,选择1.5 GHz作为肺部感染检测的工作频率.利用时间反转法确定阵列天线微波聚焦的拟定相位拟合得到最小二乘估计预测模型,初步验证了在80 mm检测深度下对感染区域的分辨率可达14 mm.测得天线的谐振频率为1.49 GHz、相对带宽为14.67%、电压驻波比为1.03,采用猪肉和肺组织凝胶进行模拟实验,结果发现采用拟定相位激励的阵列天线在待测位置处产生的磁场具有明显的聚焦效果.使用装满去离子水的直径20 mm小球模拟肺部感染,利用预测模型推断感染区域直径为25.11 mm,误差为25.55%.这些结果可为微波聚焦方法用于肺部感染快速检测提供理论和设计依据.

Based on the derivation of the magnetic field distribution generated by a planar field source within multi-layered human tissue,1.5 GHz was chosen to be the operating frequency for microwave-based pulmonary infection detection.Then the time reversal(TR)method was used to obtain the predetermined phase of the array antenna to facilitate the microwave focusing on the measured target,whereas the prediction model was obtained by using the least square estimation based on the simulation data.Preliminary verification showed that the resolution of the infected region is as high as 14 mm at the subcutaneous depth of 80 mm.The resonant frequency,the relative bandwidth and the voltage standing wave ratio of the antenna prototype were measured to be 1.49 GHz,14.67%,and 1.03,respectively.Moreover,an ex vivo experiment was carried out by using pork and lung-mimicking gel,whereas the result showed that the array antenna excited by the TR-based phases produced a focused field at the target location.Furthermore,a 20 mm diameter pellet filled with deionized water was used to simulate an infected region,which was determined by the prediction model to be 25.11 mm in diameter with an error of 25.55%.These results can provide theoretical foundation and design guidelines for the application of the microwave focusing method in the rapid detection of pulmonary infections.

徐琦;王茂州;赵书杰;黎定康

华中科技大学人工智能与自动化学院,湖北 武汉 430074华中科技大学人工智能与自动化学院,湖北 武汉 430074华中科技大学人工智能与自动化学院,湖北 武汉 430074华中科技大学人工智能与自动化学院,湖北 武汉 430074

信息技术与安全科学

肺部感染检测微波聚焦阵列天线时间反转法最小二乘估计

pulmonary infection detectionfocused microwavearray antennatime reversal methodleast squares estimation

《华中科技大学学报(自然科学版)》 2026 (9)

61-68,8

国家自然科学基金资助项目(61771210).

10.13245/j.hust.250459

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