J. M. Bauer, N. A. Alvarez, D. McPherson, R. A. Stein
{"title":"高频超声心动图图像的计算机辅助分割","authors":"J. M. Bauer, N. A. Alvarez, D. McPherson, R. A. Stein","doi":"10.1109/IEMBS.1988.94604","DOIUrl":null,"url":null,"abstract":"Segmentation of coronary arterial lumen and wall boundaries in high-frequency echocardiographic (HFE) images has been hampered by operator bias and prolonged time required for manual segmentation methods. To overcome these problems, a two-part computer algorithm has been developed to aid HFE image segmentation. This algorithm is accurate when compared to manual methods and histologic data.<<ETX>>","PeriodicalId":227170,"journal":{"name":"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1988-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Computer aided segmentation of high frequency echocardiographic images\",\"authors\":\"J. M. Bauer, N. A. Alvarez, D. McPherson, R. A. Stein\",\"doi\":\"10.1109/IEMBS.1988.94604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation of coronary arterial lumen and wall boundaries in high-frequency echocardiographic (HFE) images has been hampered by operator bias and prolonged time required for manual segmentation methods. To overcome these problems, a two-part computer algorithm has been developed to aid HFE image segmentation. This algorithm is accurate when compared to manual methods and histologic data.<<ETX>>\",\"PeriodicalId\":227170,\"journal\":{\"name\":\"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1988.94604\",\"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 the Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1988.94604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computer aided segmentation of high frequency echocardiographic images
Segmentation of coronary arterial lumen and wall boundaries in high-frequency echocardiographic (HFE) images has been hampered by operator bias and prolonged time required for manual segmentation methods. To overcome these problems, a two-part computer algorithm has been developed to aid HFE image segmentation. This algorithm is accurate when compared to manual methods and histologic data.<>
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