title: Local morphology fitting active contour for automatic vascular segmentation.
abstract: In this paper, we propose an active contour model using local morphology fitting for automatic vascular segmentation on 2-D angiogram. The vessel and background are fitted to fuzzy morphology maximum and minimum opening, separately, using linear structuring element with adaptive scale and orientation. The minimization of the energy associated with the active contour model is implemented within a level set framework. As in the current local model, fitting the image to local region information makes the model robust against the inhomogeneous background. Moreover, selective local estimations for fitting that are precomputed instead of updated in each contour evolution makes the evolution of level set robust again initial location compared to the current local model. The results on synthetic image and real angiogram compared with other methods are presented. It is shown that the proposed method can achieve automatic and accurate segmentation of vascular angiogram.
authors: Computer Vision Laboratory, Nanchang Hangkong University, Nanchang, 330063 China. kqsun@nchu.edu.cn
authors: Kaiqiong
authors: K
authors: Sun
authors: Zhen
authors: Z
authors: Chen
authors: Shaofeng
authors: S
authors: Jiang
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D003198:Computer Simulation; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008955:Models, Cardiovascular; D011856:Radiographic Image Enhancement