{"title":"基于知识的医学图像配准","authors":"Hui-Hua Wen, Wei-Chung Lin, Chin-Tu Chen","doi":"10.1109/IEMBS.1996.652772","DOIUrl":null,"url":null,"abstract":"Describes a new framework for surface-based medical image registration. By implementing a fuzzy logic system, this method allows the incorporation of human expert knowledge to evaluate the confidence level of two matching points using their multiple local image properties such as gradient direction and curvature. The proposed technique can be applied to both intra- and inter-subject medical image registration. It can also relax the performance requirement on the contour extraction process.","PeriodicalId":20427,"journal":{"name":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1996-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Knowledge-based medical image registration\",\"authors\":\"Hui-Hua Wen, Wei-Chung Lin, Chin-Tu Chen\",\"doi\":\"10.1109/IEMBS.1996.652772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Describes a new framework for surface-based medical image registration. By implementing a fuzzy logic system, this method allows the incorporation of human expert knowledge to evaluate the confidence level of two matching points using their multiple local image properties such as gradient direction and curvature. The proposed technique can be applied to both intra- and inter-subject medical image registration. It can also relax the performance requirement on the contour extraction process.\",\"PeriodicalId\":20427,\"journal\":{\"name\":\"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1996.652772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1996.652772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Describes a new framework for surface-based medical image registration. By implementing a fuzzy logic system, this method allows the incorporation of human expert knowledge to evaluate the confidence level of two matching points using their multiple local image properties such as gradient direction and curvature. The proposed technique can be applied to both intra- and inter-subject medical image registration. It can also relax the performance requirement on the contour extraction process.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
