{"title":"基于遗传算法的功能性MR图像配准","authors":"J. Rajapakse, B. Guojun","doi":"10.1109/ICONIP.1999.844660","DOIUrl":null,"url":null,"abstract":"Image registration is formulated as a problem of finding optimal linear intensity and spatial transformations. A genetic algorithm is proposed to find optimal parameters of the transformations. The new approach is used to register functional MR time series images of the human brain to compensate for subject head movement.","PeriodicalId":237855,"journal":{"name":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Functional MR image registration using a genetic algorithm\",\"authors\":\"J. Rajapakse, B. Guojun\",\"doi\":\"10.1109/ICONIP.1999.844660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image registration is formulated as a problem of finding optimal linear intensity and spatial transformations. A genetic algorithm is proposed to find optimal parameters of the transformations. The new approach is used to register functional MR time series images of the human brain to compensate for subject head movement.\",\"PeriodicalId\":237855,\"journal\":{\"name\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONIP.1999.844660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONIP.1999.844660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Functional MR image registration using a genetic algorithm
Image registration is formulated as a problem of finding optimal linear intensity and spatial transformations. A genetic algorithm is proposed to find optimal parameters of the transformations. The new approach is used to register functional MR time series images of the human brain to compensate for subject head movement.
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