K. Chew, Ching Yee Yong, R. Sudirman, Syvester Tan Chiang Wei
{"title":"Human brain modeling tumor detection in 2D and 3D representation using microwave signal analysis","authors":"K. Chew, Ching Yee Yong, R. Sudirman, Syvester Tan Chiang Wei","doi":"10.1109/ISCAIE.2018.8405490","DOIUrl":null,"url":null,"abstract":"The paper discussed on the development of a simulated brain model, microwave signal acquisition, signal processing, 2D and 3D representation. Phantom model is the main component in the research. A human-like brain model was simulated based on the real human brain relative permittivity, ∊r. The simulated model covered the greymatter and whitematter layers with the representative ∊r = 38 and ∊r = 28 at frequency 10 GHz. In microwave signal data acquisition process, the data were obtained based on the simulated brain model. Envelope detection, subtraction, window functions and proposed superposition technique function are applied to extract the information from the microwave signal. The subtracted microwave signals are represented in 2D and 3D representation for tumor location and size defining.","PeriodicalId":333327,"journal":{"name":"2018 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAIE.2018.8405490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The paper discussed on the development of a simulated brain model, microwave signal acquisition, signal processing, 2D and 3D representation. Phantom model is the main component in the research. A human-like brain model was simulated based on the real human brain relative permittivity, ∊r. The simulated model covered the greymatter and whitematter layers with the representative ∊r = 38 and ∊r = 28 at frequency 10 GHz. In microwave signal data acquisition process, the data were obtained based on the simulated brain model. Envelope detection, subtraction, window functions and proposed superposition technique function are applied to extract the information from the microwave signal. The subtracted microwave signals are represented in 2D and 3D representation for tumor location and size defining.