C. Tresp, M. Jagar, M. Moser, J. Hiltner, M. Fathi
{"title":"一种基于模糊知识的图像分割新方法","authors":"C. Tresp, M. Jagar, M. Moser, J. Hiltner, M. Fathi","doi":"10.1109/IJSIS.1996.565073","DOIUrl":null,"url":null,"abstract":"Within this work a method for knowledge based fuzzy image segmentation is introduced. The basic idea comes from the field of automated medical MRI segmentation where the well-known standard methods have proven insufficient to solve the task. Therefore, a method especially for the problems concerning vagueness in medical imaging has been developed. Beside the improved segmentation procedures, the development has a general impact on the conventional model of image analysis.","PeriodicalId":437491,"journal":{"name":"Proceedings IEEE International Joint Symposia on Intelligence and Systems","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A new method for image segmentation based on fuzzy knowledge\",\"authors\":\"C. Tresp, M. Jagar, M. Moser, J. Hiltner, M. Fathi\",\"doi\":\"10.1109/IJSIS.1996.565073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Within this work a method for knowledge based fuzzy image segmentation is introduced. The basic idea comes from the field of automated medical MRI segmentation where the well-known standard methods have proven insufficient to solve the task. Therefore, a method especially for the problems concerning vagueness in medical imaging has been developed. Beside the improved segmentation procedures, the development has a general impact on the conventional model of image analysis.\",\"PeriodicalId\":437491,\"journal\":{\"name\":\"Proceedings IEEE International Joint Symposia on Intelligence and Systems\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Joint Symposia on Intelligence and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJSIS.1996.565073\",\"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 IEEE International Joint Symposia on Intelligence and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJSIS.1996.565073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for image segmentation based on fuzzy knowledge
Within this work a method for knowledge based fuzzy image segmentation is introduced. The basic idea comes from the field of automated medical MRI segmentation where the well-known standard methods have proven insufficient to solve the task. Therefore, a method especially for the problems concerning vagueness in medical imaging has been developed. Beside the improved segmentation procedures, the development has a general impact on the conventional model of image analysis.
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