{"title":"噪声对数学乳房模型复介电常数重建的影响","authors":"Hardik N. Patel, Deepak K. Ghodgaonkar","doi":"10.1109/ICSMB.2016.7915077","DOIUrl":null,"url":null,"abstract":"Cancer detection in breast using microwave imaging relies on accuracy of complex permittivity reconstruction. Microwave imaging is highly sensitive to noise due to low amplitude of scattered electric field. In this paper, the effect of noise on complex permittivity reconstruction is shown using different noise scenarios. In the presence of noise, performance of our inversion method is better than iterative and regularized inversion methods","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The effect of noise on complex permittivity reconstruction in mathematical breast model\",\"authors\":\"Hardik N. Patel, Deepak K. Ghodgaonkar\",\"doi\":\"10.1109/ICSMB.2016.7915077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cancer detection in breast using microwave imaging relies on accuracy of complex permittivity reconstruction. Microwave imaging is highly sensitive to noise due to low amplitude of scattered electric field. In this paper, the effect of noise on complex permittivity reconstruction is shown using different noise scenarios. In the presence of noise, performance of our inversion method is better than iterative and regularized inversion methods\",\"PeriodicalId\":231556,\"journal\":{\"name\":\"2016 International Conference on Systems in Medicine and Biology (ICSMB)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Systems in Medicine and Biology (ICSMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSMB.2016.7915077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMB.2016.7915077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The effect of noise on complex permittivity reconstruction in mathematical breast model
Cancer detection in breast using microwave imaging relies on accuracy of complex permittivity reconstruction. Microwave imaging is highly sensitive to noise due to low amplitude of scattered electric field. In this paper, the effect of noise on complex permittivity reconstruction is shown using different noise scenarios. In the presence of noise, performance of our inversion method is better than iterative and regularized inversion methods