F. M. Greene, K. Beach, D. Phillips, J. Primozich, D. Strandness
{"title":"脉冲多普勒超声对颈动脉疾病的模式识别","authors":"F. M. Greene, K. Beach, D. Phillips, J. Primozich, D. Strandness","doi":"10.1109/IEMBS.1988.94491","DOIUrl":null,"url":null,"abstract":"Computer pattern recognition of carotid artery atherosclerosis has been implemented in dedicated systems. Accuracy is equivalent to that of an expert sonographer and is repeatable for different sonographers. The system uses algorithms which were systematically trained from a database of 318 cases having arteriographic confirmation, plus 88 asymptomatic normals. A software language was implemented to aid in maintaining the system.<<ETX>>","PeriodicalId":227170,"journal":{"name":"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pattern recognition of carotid artery diseases using pulsed Doppler ultrasound\",\"authors\":\"F. M. Greene, K. Beach, D. Phillips, J. Primozich, D. Strandness\",\"doi\":\"10.1109/IEMBS.1988.94491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computer pattern recognition of carotid artery atherosclerosis has been implemented in dedicated systems. Accuracy is equivalent to that of an expert sonographer and is repeatable for different sonographers. The system uses algorithms which were systematically trained from a database of 318 cases having arteriographic confirmation, plus 88 asymptomatic normals. A software language was implemented to aid in maintaining the system.<<ETX>>\",\"PeriodicalId\":227170,\"journal\":{\"name\":\"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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.1988.94491\",\"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.1988.94491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern recognition of carotid artery diseases using pulsed Doppler ultrasound
Computer pattern recognition of carotid artery atherosclerosis has been implemented in dedicated systems. Accuracy is equivalent to that of an expert sonographer and is repeatable for different sonographers. The system uses algorithms which were systematically trained from a database of 318 cases having arteriographic confirmation, plus 88 asymptomatic normals. A software language was implemented to aid in maintaining the system.<>
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