Title :
A Novel Method of Vessel Segmentation for X-ray Coronary Angiography Images
Author :
Li, Yanli ; Zhou, Shoujun ; Wu, Jianhuang ; Ma, Xin ; Peng, Kewen
Author_Institution :
Shenzhen Inst. of Adv. Technol., Shenzhen, China
Abstract :
This paper presents a new automatic region-growing method for vessel segmentation in two-dimensional X-ray coronary angiography images. The method consists of two parts: the feature map extraction based on a novel vesselness function; and the segmentation process which includes automatic seed-point selection, main branch segmentation and vessel detail repair. Both the greyscale and spatial information are extracted for segmentation based on region growing algorithm. The presented method is validated on several clinical X-ray coronary angiography images, and the experimental results show that the method can not only segment large vessels but also small vessels.
Keywords :
angiocardiography; blood vessels; diagnostic radiography; feature extraction; image segmentation; medical image processing; 2D clinical X-ray coronary angiography images; automatic region-growing method; automatic seed-point selection; feature map extraction; main branch segmentation; vessel detail repair; vessel segmentation; vesselness function;; Angiography; Feature extraction; Gray-scale; Image segmentation; Maintenance engineering; X-ray imaging; X-ray coronary angiography; region-growing; vessel segmentation; vesselness function;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.34
