{"title":"基于皮肤表面反射和神经网络的微波乳房成像复介电常数重建","authors":"Peixian Zhu;Shouhei Kidera","doi":"10.1109/JERM.2023.3321423","DOIUrl":null,"url":null,"abstract":"This study introduces an experimental validation for the complex permittivity profile reconstruction using the multi-layer perceptron (MLP) neural network (NN) approach for quantitative microwave recognition of breast cancer. A direct conversion from the four-dimensional scattered data to the complex permittivity three-dimensional profile can be achieved by combining the MLP-NN and the skin surface rejection preprocessing. The experimental data, measured by ultra-wideband radar equipment using a simplified breast phantom, validates that our approach provides both the real and imaginary parts of complex permittivity profiles, even when using limited numbers of training datasets.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 4","pages":"425-431"},"PeriodicalIF":3.0000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Complex Permittivity Reconstruction Using Skin Surface Reflection and Neural Network for Microwave Breast Imaging\",\"authors\":\"Peixian Zhu;Shouhei Kidera\",\"doi\":\"10.1109/JERM.2023.3321423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study introduces an experimental validation for the complex permittivity profile reconstruction using the multi-layer perceptron (MLP) neural network (NN) approach for quantitative microwave recognition of breast cancer. A direct conversion from the four-dimensional scattered data to the complex permittivity three-dimensional profile can be achieved by combining the MLP-NN and the skin surface rejection preprocessing. The experimental data, measured by ultra-wideband radar equipment using a simplified breast phantom, validates that our approach provides both the real and imaginary parts of complex permittivity profiles, even when using limited numbers of training datasets.\",\"PeriodicalId\":29955,\"journal\":{\"name\":\"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology\",\"volume\":\"7 4\",\"pages\":\"425-431\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10286040/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10286040/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Complex Permittivity Reconstruction Using Skin Surface Reflection and Neural Network for Microwave Breast Imaging
This study introduces an experimental validation for the complex permittivity profile reconstruction using the multi-layer perceptron (MLP) neural network (NN) approach for quantitative microwave recognition of breast cancer. A direct conversion from the four-dimensional scattered data to the complex permittivity three-dimensional profile can be achieved by combining the MLP-NN and the skin surface rejection preprocessing. The experimental data, measured by ultra-wideband radar equipment using a simplified breast phantom, validates that our approach provides both the real and imaginary parts of complex permittivity profiles, even when using limited numbers of training datasets.