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
         
        
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
         
        
            Conference_Location : 
Tianjin
         
        
        
            DOI : 
10.1109/ICMLC.2013.6890455