{"title":"基于内容的医学图像检索中统计空间方法的特征提取","authors":"B. Ergen, M. Baykara","doi":"10.1109/BIYOMUT.2010.5479763","DOIUrl":null,"url":null,"abstract":"Content based image retrieval systems are used widespread for general purpose image archiving, and the developments are still continued it. But it is not widely used for archiving medical images. In presented, it is examined the retrieval efficiency rate of statistical spatial methods used for feature extraction in general purpose images. The investigated algorithms depend on GLCM and GLRLM accepted as spatial methods. The results obtained in this study shows that queries based on statistics obtained from GLCM are more satisfier.","PeriodicalId":180275,"journal":{"name":"2010 15th National Biomedical Engineering Meeting","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Feature extraction of using statistical spatial methods for content based medical image retrieval\",\"authors\":\"B. Ergen, M. Baykara\",\"doi\":\"10.1109/BIYOMUT.2010.5479763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Content based image retrieval systems are used widespread for general purpose image archiving, and the developments are still continued it. But it is not widely used for archiving medical images. In presented, it is examined the retrieval efficiency rate of statistical spatial methods used for feature extraction in general purpose images. The investigated algorithms depend on GLCM and GLRLM accepted as spatial methods. The results obtained in this study shows that queries based on statistics obtained from GLCM are more satisfier.\",\"PeriodicalId\":180275,\"journal\":{\"name\":\"2010 15th National Biomedical Engineering Meeting\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 15th National Biomedical Engineering Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIYOMUT.2010.5479763\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 15th National Biomedical Engineering Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIYOMUT.2010.5479763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature extraction of using statistical spatial methods for content based medical image retrieval
Content based image retrieval systems are used widespread for general purpose image archiving, and the developments are still continued it. But it is not widely used for archiving medical images. In presented, it is examined the retrieval efficiency rate of statistical spatial methods used for feature extraction in general purpose images. The investigated algorithms depend on GLCM and GLRLM accepted as spatial methods. The results obtained in this study shows that queries based on statistics obtained from GLCM are more satisfier.