Title :
Automatic Segmentation of Abdominal Aortic Aneurysm Using Logical Algorithm
Author :
Hosseini, Behnam ; Mashak, Saeed Vahabi ; Majd, Emadaldin Mozafari ; Sheikh, U.U. ; Abu-Bakar, S.A.R.
Author_Institution :
Dept. of Microelectron. & Comput. Eng., Video & Image Process. (CvviP) Res. Group, Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
Abdominal aortic aneurysm is a cardiovascular disease which occurs due to an abnormal weakening of the aorta wall. This failure in aortic wall causes the inner layer to be ruptured because of excessive blood pressure. Consequently, the blood flows into the space between lumen and epithelial, hence a thrombus is generated. On the other hand, excessive growth in the aorta diameter can lead to death as a result of a rupture in the epithelial. In this paper, we present a technique for automatic segmentation of abdominal aortic aneurysm. The proposed method integrates the exclusive information extracted from histogram and morphological properties of aortic lumen to segment the aorta. Then the proposed algorithm utilizes a search technique with priori information about the lumen to segment epithelial area automatically.
Keywords :
cardiovascular system; diseases; haemodynamics; image segmentation; knowledge acquisition; medical image processing; abdominal aortic aneurysm; automatic segmentation; blood flow; blood pressure; cardiovascular disease; information extraction; logical algorithm; lumen; priori information; search technique; segment epithelial area; thrombus; abdominal aortic aneurysm; epithelial; histogram; lumen; segmentation;
Conference_Titel :
Computer Modeling and Simulation (EMS), 2010 Fourth UKSim European Symposium on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-9313-5
Electronic_ISBN :
978-0-7695-4308-6
DOI :
10.1109/EMS.2010.35