Title :
Segmentation and Tracking of Coronary Artery Using Graph-Cut in CT Angiographic
Author :
Li, Meng ; He, Huiguang ; Yi, Jianhua ; Lv, Bin ; Zhao, Mingchang
Author_Institution :
Key Lab. of Complex Syst. & Intell. Sci., Chinese Acad. of Sci., Beijing, China
Abstract :
This paper presents a semiautomatic method to detect the coronary arteries in X-ray CT angiography (CTA) images with simple user interaction. The algorithm is started with performing modified Otsu threshold method and clustering of superpixel to reconstruct the image. The interactive graph cut segmentation and an improved top-hat filter is used to extract the coronary artery in series of two dimension (2D) slice images. Finally, coronary artery tree is tracked with a method based on region average shift. The accuracy of coronary artery extraction has been validated in 16 CTA datasets. The results demonstrate this algorithm has satisfactory speed and efficiency. With more user interaction, the method can be easily extended to the arteries that are not detected automatically.
Keywords :
computerised tomography; image reconstruction; image segmentation; medical image processing; 2D slice images; X-ray CT angiography; coronary artery segmentation; coronary artery tracking; graph cut; image reconstruct ion; modified Otsu threshold; Angiography; Arteries; Clustering algorithms; Computed tomography; Filters; Image reconstruction; Image segmentation; X-ray detection; X-ray detectors; X-ray imaging;
Conference_Titel :
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4132-7
Electronic_ISBN :
978-1-4244-4134-1
DOI :
10.1109/BMEI.2009.5305720
