{"title":"模糊逻辑在多智能体脑图像分割中的应用","authors":"S. Nasser, R. Mekki","doi":"10.1109/ICoSC.2013.6750826","DOIUrl":null,"url":null,"abstract":"The segmentation of medical images is a new technology, rich and varied, but in which many existing methods are difficult to apply to real problems. In this work, we present a segmentation system for brain MRI images that is based on two approaches method “growth area” and “FCM” algorithm for each of these approaches, we will explain and illustrate their usefulness. The proposed system aims to improve the segmentation of brain images to classify the three components of the human brain matter in a clearer way in a multi-agent environment.","PeriodicalId":199135,"journal":{"name":"3rd International Conference on Systems and Control","volume":"407 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Use of fuzzy logic for segmenting of brain images by multi-agent system\",\"authors\":\"S. Nasser, R. Mekki\",\"doi\":\"10.1109/ICoSC.2013.6750826\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The segmentation of medical images is a new technology, rich and varied, but in which many existing methods are difficult to apply to real problems. In this work, we present a segmentation system for brain MRI images that is based on two approaches method “growth area” and “FCM” algorithm for each of these approaches, we will explain and illustrate their usefulness. The proposed system aims to improve the segmentation of brain images to classify the three components of the human brain matter in a clearer way in a multi-agent environment.\",\"PeriodicalId\":199135,\"journal\":{\"name\":\"3rd International Conference on Systems and Control\",\"volume\":\"407 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3rd International Conference on Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICoSC.2013.6750826\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Conference on Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoSC.2013.6750826","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use of fuzzy logic for segmenting of brain images by multi-agent system
The segmentation of medical images is a new technology, rich and varied, but in which many existing methods are difficult to apply to real problems. In this work, we present a segmentation system for brain MRI images that is based on two approaches method “growth area” and “FCM” algorithm for each of these approaches, we will explain and illustrate their usefulness. The proposed system aims to improve the segmentation of brain images to classify the three components of the human brain matter in a clearer way in a multi-agent environment.