{"title":"An Improved Holographic Microwave Breast Imaging Based on Deep Neural Network","authors":"Lulu Wang","doi":"10.1115/imece2019-10910","DOIUrl":null,"url":null,"abstract":"\n Microwave imaging offers excellent potential for breast cancer detection. Deep learning is state-of-the-art in biomedical imaging, which has been successfully applied for biomedical image classifications. This paper investigates a deep neural network (DNN) based classification method for identifying breast lesion in holographic microwave image (HMI). A computer model is developed to demonstrate the proposed method under practical consideration. Various experiments are carried out to evaluate the proposed DNN-based HMI for breast lesion classification. Results have shown that the proposed method could serve as a helpful imaging tool for automatically classifying different types of breast tissues.","PeriodicalId":332737,"journal":{"name":"Volume 3: Biomedical and Biotechnology Engineering","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 3: Biomedical and Biotechnology Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2019-10910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Microwave imaging offers excellent potential for breast cancer detection. Deep learning is state-of-the-art in biomedical imaging, which has been successfully applied for biomedical image classifications. This paper investigates a deep neural network (DNN) based classification method for identifying breast lesion in holographic microwave image (HMI). A computer model is developed to demonstrate the proposed method under practical consideration. Various experiments are carried out to evaluate the proposed DNN-based HMI for breast lesion classification. Results have shown that the proposed method could serve as a helpful imaging tool for automatically classifying different types of breast tissues.