{"title":"胸部CT扫描的恶性胸膜间皮瘤分割","authors":"Wael Brahim, M. Mestiri, N. Betrouni, K. Hamrouni","doi":"10.1109/ATSIP.2017.8075605","DOIUrl":null,"url":null,"abstract":"In this paper, a texture-based segmentation method of the Malignant Pleural Mesothelioma from thoracic CT scans is presented. For the texture analysis part, we have used an automatic sampling and a manual sampling to extract statistical features from the MPM texture. For the segmentation stage, the method iterates the whole CT volume and selects pixels satisfying the extracted statistical criteria. The assessment of the proposed method showed an acceptable degree of similarity rate (J=0.73) between the ground truth and the generated MPM volume.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Malignant pleural mesothelioma segmentation from thoracic CT scans\",\"authors\":\"Wael Brahim, M. Mestiri, N. Betrouni, K. Hamrouni\",\"doi\":\"10.1109/ATSIP.2017.8075605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a texture-based segmentation method of the Malignant Pleural Mesothelioma from thoracic CT scans is presented. For the texture analysis part, we have used an automatic sampling and a manual sampling to extract statistical features from the MPM texture. For the segmentation stage, the method iterates the whole CT volume and selects pixels satisfying the extracted statistical criteria. The assessment of the proposed method showed an acceptable degree of similarity rate (J=0.73) between the ground truth and the generated MPM volume.\",\"PeriodicalId\":259951,\"journal\":{\"name\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATSIP.2017.8075605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP.2017.8075605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Malignant pleural mesothelioma segmentation from thoracic CT scans
In this paper, a texture-based segmentation method of the Malignant Pleural Mesothelioma from thoracic CT scans is presented. For the texture analysis part, we have used an automatic sampling and a manual sampling to extract statistical features from the MPM texture. For the segmentation stage, the method iterates the whole CT volume and selects pixels satisfying the extracted statistical criteria. The assessment of the proposed method showed an acceptable degree of similarity rate (J=0.73) between the ground truth and the generated MPM volume.