R. Zaouche, Ahror Belaid, Bassel Solaiman, D. Salem, S. Tliba
{"title":"基于生长区域和水平集技术的低级别胶质瘤分割","authors":"R. Zaouche, Ahror Belaid, Bassel Solaiman, D. Salem, S. Tliba","doi":"10.1109/ATSIP.2018.8364479","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel semi-automatic segmentation method based on the local image properties. Its originality is twofold, the first stands on the intensity invariant of phase-local information for the purpose of low-grade gliomas segmentation in MR images. In a second time, a level set method driven is combined to growing region so as to improve tumor detection. Experiments were conducted on a set of medical images. A comparison between the obtained results and the manual segmentation collected from experts is performed. The preliminary results are interesting and encouraging.","PeriodicalId":332253,"journal":{"name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Segmentation of low-grade gliomas based on the growing region and level sets techniques\",\"authors\":\"R. Zaouche, Ahror Belaid, Bassel Solaiman, D. Salem, S. Tliba\",\"doi\":\"10.1109/ATSIP.2018.8364479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a novel semi-automatic segmentation method based on the local image properties. Its originality is twofold, the first stands on the intensity invariant of phase-local information for the purpose of low-grade gliomas segmentation in MR images. In a second time, a level set method driven is combined to growing region so as to improve tumor detection. Experiments were conducted on a set of medical images. A comparison between the obtained results and the manual segmentation collected from experts is performed. The preliminary results are interesting and encouraging.\",\"PeriodicalId\":332253,\"journal\":{\"name\":\"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATSIP.2018.8364479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP.2018.8364479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation of low-grade gliomas based on the growing region and level sets techniques
In this paper, we propose a novel semi-automatic segmentation method based on the local image properties. Its originality is twofold, the first stands on the intensity invariant of phase-local information for the purpose of low-grade gliomas segmentation in MR images. In a second time, a level set method driven is combined to growing region so as to improve tumor detection. Experiments were conducted on a set of medical images. A comparison between the obtained results and the manual segmentation collected from experts is performed. The preliminary results are interesting and encouraging.