{"title":"基于分割的目标标记算法的脑肿瘤检测","authors":"Amitava Halder, C. Giri, A. Halder","doi":"10.1109/ICECI.2014.6767389","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an efficient brain tumor detection method, which can detect tumor and locate it in the brain MRI images. This method extracts the tumor by using K-means algorithm followed by Object labeling algorithm. Also, some preprocessing steps (median filtering and morphological operation) are used for tumor detection purpose. It is observed that the experimental results of the proposed method gives better result in comparison to other techniques.","PeriodicalId":315219,"journal":{"name":"International Conference on Electronics, Communication and Instrumentation (ICECI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Brain tumor detection using segmentation based Object labeling algorithm\",\"authors\":\"Amitava Halder, C. Giri, A. Halder\",\"doi\":\"10.1109/ICECI.2014.6767389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an efficient brain tumor detection method, which can detect tumor and locate it in the brain MRI images. This method extracts the tumor by using K-means algorithm followed by Object labeling algorithm. Also, some preprocessing steps (median filtering and morphological operation) are used for tumor detection purpose. It is observed that the experimental results of the proposed method gives better result in comparison to other techniques.\",\"PeriodicalId\":315219,\"journal\":{\"name\":\"International Conference on Electronics, Communication and Instrumentation (ICECI)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Electronics, Communication and Instrumentation (ICECI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECI.2014.6767389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Electronics, Communication and Instrumentation (ICECI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECI.2014.6767389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Brain tumor detection using segmentation based Object labeling algorithm
In this paper, we propose an efficient brain tumor detection method, which can detect tumor and locate it in the brain MRI images. This method extracts the tumor by using K-means algorithm followed by Object labeling algorithm. Also, some preprocessing steps (median filtering and morphological operation) are used for tumor detection purpose. It is observed that the experimental results of the proposed method gives better result in comparison to other techniques.