Title :
Skeleton extraction of cerebral vascular image based on level set model
Author :
Zhang, Guofang ; Feng, Da ming
Author_Institution :
Dept. of Comput. Eng., Henan Ind. & Trade Vocational Collage, Zhengzhou, China
Abstract :
This paper presents a new framework to calculate the continuous brain blood vessel skeleton curve of binary images and gray-scale images. The main idea of the method is: the minimum cost path between any two skeleton points is a skeleton line. Algorithm using two different intermediate functions, one is Euclidean distance field and another is deformed gradient vector flow, gained two different energy function respectively proportional to them. The topology nodes from first energy function control the shape of the object, and the second one control skeleton extraction using topology nodes as the source points. Experiment and analysis can verify the validity and robustness of this method, and not sensitive to the boundary noise.
Keywords :
blood vessels; bone; brain; feature extraction; gradient methods; medical image processing; Euclidean distance field; binary images; boundary noise; cerebral vascular image; continuous brain blood vessel skeleton curve; deformed gradient vector flow; energy function; gray-scale images; level set model; minimum cost path; skeleton extraction; topology nodes; Algorithm design and analysis; Data mining; Mathematical model; Shape; Skeleton; Surface waves; Topology; Level Set Model; binary image and gray-scale image; minimum cost path; skeleton extraction; topology node;
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6495-1
DOI :
10.1109/BMEI.2010.5640005