基于微波技术的脑出血检测系统
Cerebral hemorrhage detection system using microwave technology
杨义龙 1冯逸飞 2朱刘凤 3刘意 3何颖2
作者信息
- 1. 上海理工大学健康科学与工程学院,上海 200093;海军特色医学中心,上海 200433
- 2. 海军特色医学中心,上海 200433
- 3. 上海理工大学健康科学与工程学院,上海 200093
- 折叠
摘要
目的:针对微波检测系统存在设备价格昂贵、天线选通开关系统复杂和天线通道冗余等问题,设计优化脑出血检测系统.方法:采用最简贴片天线结构,应用射频开关芯片策略,对天线选通开关系统和通道数量进行优化.通过优化后的检测系统对模拟脑出血物进行采样检测;同时,运用模式识别的方法来区分是否脑出血.结果:XGBoost算法模型在脑出血识别任务中展现出优越的效果,其在测试集上准确率达到1.000,K折交叉验证的平均准确率高达0.973,并且训练集准确率为0.996.结论:优化的脑出血检测系统具有较高的检测精度和可靠性,具备识别脑出血的潜力.
Abstract
Objective To design and optimize the detection system for cerebral hemorrhage for overcoming the limitations in microwave detection system,such as expensive equipment,complex antenna gating switch system and redundant antenna channels.Methods The system adopted the simplest patch antenna structure,optimized the antenna gating switch system and reduced the number of channels by radiofrequency switch chip strategy.The simulated cerebral hemorrhage was sampled and detected through the optimized detection system;and pattern recognition method was used to distinguish whether there was cerebral hemorrhage.Results XGBoost algorithm model showed superior performance in the task of cerebral hemorrhage recognition,with an accuracy of 1.000 on the test set,an average accuracy of 0.973 in K-fold cross-validation,and an accuracy of 0.996 on the training set.Conclusion The optimized cerebral hemorrhage detection system which has high detection accuracy and reliability has the potential to identify cerebral hemorrhage.
关键词
脑出血/微波检测/系统优化/XGBoost算法Key words
cerebral hemorrhage/microwave detection/system optimization/XGBoost algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据