Title :
Fast and Automatic Segmentation of Ascending Aorta in MSCT Volume Data
Author :
Wang, Shengjun ; Fu, Ling ; Yue, Yong ; Kang, Yan ; Liu, Jiren
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
The segmentation of the ascending aorta from multislice computed tomography (MSCT) volume data is one of the critical steps for the quantitative analysis coronary artery. In this paper, a fast and automatic iterative method is presented. The method locates the volume of interest (VOI) of the ascending aorta and detects the seed point automatically. Then an automatic iterative procedure is implemented adaptively to segment the aorta slice by slice. The method was evaluated in various clinical datasets using three criteria: the sensitivity to noise, the successful rate and the running time. Experiments show that the method is robust and achieves a successful rate as high as 95.1% within 1.5 second in average.
Keywords :
cardiology; computerised tomography; image segmentation; iterative methods; medical image processing; MSCT volume data; ascending aorta segmentation; iterative method; multislice computed tomography; quantitative analysis coronary artery; Arteries; Biomedical engineering; Biomedical imaging; Cardiac disease; Cardiovascular diseases; Computed tomography; Image segmentation; Information analysis; Information science; Iterative methods;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5305569