S. Khoor, F. Szaboki, J. Nieberl, M. Khoor, E. Kékes
{"title":"基于速度图的超声心动图边缘检测新方法","authors":"S. Khoor, F. Szaboki, J. Nieberl, M. Khoor, E. Kékes","doi":"10.1109/CIC.1993.378325","DOIUrl":null,"url":null,"abstract":"The authors' automated image processing method creates the velocity maps of the small regions of echocardiographic 2D images. The separation and matching of this objects are based on their velocity profiles. The object-oriented programming method allows the handling such a complex problem. The automated analysis showed a good performance comparing with the traditional wall motion detection: the specificity of computer scoring was 84.4%, the sensitivity 81.2%.<<ETX>>","PeriodicalId":20445,"journal":{"name":"Proceedings of Computers in Cardiology Conference","volume":"59 1","pages":"623-626"},"PeriodicalIF":0.0000,"publicationDate":"1993-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new method of echocardiographic edge detection using velocity maps\",\"authors\":\"S. Khoor, F. Szaboki, J. Nieberl, M. Khoor, E. Kékes\",\"doi\":\"10.1109/CIC.1993.378325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors' automated image processing method creates the velocity maps of the small regions of echocardiographic 2D images. The separation and matching of this objects are based on their velocity profiles. The object-oriented programming method allows the handling such a complex problem. The automated analysis showed a good performance comparing with the traditional wall motion detection: the specificity of computer scoring was 84.4%, the sensitivity 81.2%.<<ETX>>\",\"PeriodicalId\":20445,\"journal\":{\"name\":\"Proceedings of Computers in Cardiology Conference\",\"volume\":\"59 1\",\"pages\":\"623-626\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Computers in Cardiology Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.1993.378325\",\"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 Computers in Cardiology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.1993.378325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method of echocardiographic edge detection using velocity maps
The authors' automated image processing method creates the velocity maps of the small regions of echocardiographic 2D images. The separation and matching of this objects are based on their velocity profiles. The object-oriented programming method allows the handling such a complex problem. The automated analysis showed a good performance comparing with the traditional wall motion detection: the specificity of computer scoring was 84.4%, the sensitivity 81.2%.<>
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
