{"title":"基于RBF神经网络的白细胞五种分类系统设计","authors":"Wei Long, Lixia Wan, Xingyuan Zhang, B. Lu","doi":"10.12733/JICS20105744","DOIUrl":null,"url":null,"abstract":"In recent year, the ve classication for WBC in hematology analyzers are mostly implemented by hardware mode, those instruments are excessively rely on the accuracy of some components, and the hardware structure is complex, which limit the further development of the ve classication hematology analyzer. Therefore, a ve classication system for WBC based on RBF neural network is put forward, which takes the full-optical technology as the WBC detection method, and uses VC6.0 as the software development platform to establish the RBF neural network model for the recognition and ve classication of WBC. The experimental results show the recognition accuracy of the instrument equipped with the system is close to Mythic 22 which is a high-grade ve classication hematology analyzer. Conclusions: The ve classication system for WBC proposed has the features of reliable performance and high degree of accuracy.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Design of Five Classification System for WBC Based on RBF Neural Network\",\"authors\":\"Wei Long, Lixia Wan, Xingyuan Zhang, B. Lu\",\"doi\":\"10.12733/JICS20105744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent year, the ve classication for WBC in hematology analyzers are mostly implemented by hardware mode, those instruments are excessively rely on the accuracy of some components, and the hardware structure is complex, which limit the further development of the ve classication hematology analyzer. Therefore, a ve classication system for WBC based on RBF neural network is put forward, which takes the full-optical technology as the WBC detection method, and uses VC6.0 as the software development platform to establish the RBF neural network model for the recognition and ve classication of WBC. The experimental results show the recognition accuracy of the instrument equipped with the system is close to Mythic 22 which is a high-grade ve classication hematology analyzer. Conclusions: The ve classication system for WBC proposed has the features of reliable performance and high degree of accuracy.\",\"PeriodicalId\":213716,\"journal\":{\"name\":\"The Journal of Information and Computational Science\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Information and Computational Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12733/JICS20105744\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Information and Computational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12733/JICS20105744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Design of Five Classification System for WBC Based on RBF Neural Network
In recent year, the ve classication for WBC in hematology analyzers are mostly implemented by hardware mode, those instruments are excessively rely on the accuracy of some components, and the hardware structure is complex, which limit the further development of the ve classication hematology analyzer. Therefore, a ve classication system for WBC based on RBF neural network is put forward, which takes the full-optical technology as the WBC detection method, and uses VC6.0 as the software development platform to establish the RBF neural network model for the recognition and ve classication of WBC. The experimental results show the recognition accuracy of the instrument equipped with the system is close to Mythic 22 which is a high-grade ve classication hematology analyzer. Conclusions: The ve classication system for WBC proposed has the features of reliable performance and high degree of accuracy.