{"title":"基于双树复小波变换和自适应高斯隶属函数的PET-CT融合算法","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":"{\"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}","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}
A fusion algorithm of PET-CT based on dual-tree complex wavelet transform and self-adaption Gaussian membership function
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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