Emadaldin Mozafari Majd, U. U. Sheikh, S. Abu-Bakar
{"title":"Automatic Segmentation of Abdominal Aortic Aneurysm in Computed Tomography Images Using Spatial Fuzzy C-Means","authors":"Emadaldin Mozafari Majd, U. U. Sheikh, S. Abu-Bakar","doi":"10.1109/SITIS.2010.38","DOIUrl":null,"url":null,"abstract":"Abdominal aortic aneurysm (AAA) is a cardiovascular disease which mostly appears in elderly people. Due to the weakening of aortic wall, a rupture occurs in the most inner layer of aorta and a thrombus is generated. If the diameter exceeds greater than 5.5 cm, a treatment strategy is required. As a result, CT imaging is utilized to screen and evaluate thrombus parameters for treatment. Exploitation of automatic techniques improves the pre- and post-treatment evaluation. In this paper, at first an algorithm based on spatial fuzzy c-means is applied to the CT image. Then lumen and thrombus are segmented automatically by tuning of morphological operators and thresholding parameters.","PeriodicalId":128396,"journal":{"name":"2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems","volume":"12 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2010.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Abdominal aortic aneurysm (AAA) is a cardiovascular disease which mostly appears in elderly people. Due to the weakening of aortic wall, a rupture occurs in the most inner layer of aorta and a thrombus is generated. If the diameter exceeds greater than 5.5 cm, a treatment strategy is required. As a result, CT imaging is utilized to screen and evaluate thrombus parameters for treatment. Exploitation of automatic techniques improves the pre- and post-treatment evaluation. In this paper, at first an algorithm based on spatial fuzzy c-means is applied to the CT image. Then lumen and thrombus are segmented automatically by tuning of morphological operators and thresholding parameters.