{"title":"一种有效的磁共振图像脑肿瘤分割框架","authors":"S. Bourouis, K. Hamrouni","doi":"10.1109/IPTA.2008.4743791","DOIUrl":null,"url":null,"abstract":"The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a region-based level-set approach and some conventional methods. Our proposed approach produces good results and decreases processing time. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.","PeriodicalId":384072,"journal":{"name":"2008 First Workshops on Image Processing Theory, Tools and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"An Efficient Framework for Brain Tumor Segmentation in Magnetic Resonance Images\",\"authors\":\"S. Bourouis, K. Hamrouni\",\"doi\":\"10.1109/IPTA.2008.4743791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a region-based level-set approach and some conventional methods. Our proposed approach produces good results and decreases processing time. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.\",\"PeriodicalId\":384072,\"journal\":{\"name\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 First Workshops on Image Processing Theory, Tools and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2008.4743791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First Workshops on Image Processing Theory, Tools and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2008.4743791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient Framework for Brain Tumor Segmentation in Magnetic Resonance Images
The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a region-based level-set approach and some conventional methods. Our proposed approach produces good results and decreases processing time. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
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