DocumentCode :
3115259
Title :
A novel method for vessel skeleton extraction
Author :
Pengyue Zhang ; Xinhua You ; Duanquan Xu
Author_Institution :
Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
01
fYear :
2013
fDate :
14-17 July 2013
Firstpage :
118
Lastpage :
123
Abstract :
A novel vessel skeleton extraction method is presented in this work. Our work consists of three steps in a coarse-to-fine style: Firstly, by modeling the distance transform and its gradient vector field, the average outward flux of the gradient vector field is computed to coarsely label all image points. Then we introduce a topology-based shape thinning algorithm for extracting vessel skeleton tree. At last, a skeleton tree refinement algorithm is applied to get a precise extraction of vessel skeleton. The proposed method is parameter-free and computationally efficient. The validity and efficiency of the method is tested on two public database of human eye retina vessel images.
Keywords :
feature extraction; image segmentation; image thinning; trees (mathematics); average outward flux; coarse-to-fine method; coarsely labelled image points; distance transform modeling; gradient vector field modeling; human eye retina vessel image database; parameter-free computationally efficient method; skeleton tree refinement algorithm; topology-based shape thinning algorithm; vessel skeleton extraction method; vessel skeleton tree extraction; Abstracts; Databases; Image color analysis; Image segmentation; Skeleton; Average Outward Flux; Segmentation; Vessel Skeleton;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
Type :
conf
DOI :
10.1109/ICMLC.2013.6890455
Filename :
6890455
Link To Document :
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