{"title":"A fusion algorithm of PET-CT based on dual-tree complex wavelet transform and self-adaption Gaussian membership function","authors":"Xingyu Wei, T. Zhou, Huiling Lu","doi":"10.1109/ICOT.2014.6956638","DOIUrl":null,"url":null,"abstract":"This article proposed a new fusion algorithm of PET/CT based on dual-tree complex wavelet transform and self-adaption Gaussian membership function. Firstly, preprocessed and registered PET and CT image of non-small cell lung cancer. Secondly, used dual-tree complex wavelet transform to decompose PET and CT image in order to get the low-frequency and high-frequency components. Thirdly, using self-adaption Gaussian membership function to fuse low-frequency components. Finally, using two experiments to verify validity and feasibility of the proposed algorithm. The experiments results shown that the algorithm is efficiency.","PeriodicalId":343641,"journal":{"name":"2014 International Conference on Orange Technologies","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Orange Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOT.2014.6956638","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
This article proposed a new fusion algorithm of PET/CT based on dual-tree complex wavelet transform and self-adaption Gaussian membership function. Firstly, preprocessed and registered PET and CT image of non-small cell lung cancer. Secondly, used dual-tree complex wavelet transform to decompose PET and CT image in order to get the low-frequency and high-frequency components. Thirdly, using self-adaption Gaussian membership function to fuse low-frequency components. Finally, using two experiments to verify validity and feasibility of the proposed algorithm. The experiments results shown that the algorithm is efficiency.
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