Title :
A level set method for retina image vessel segmentation based on the local cluster value via bias correction
Author :
Haiming Gongt;Yan Li;Gaoqiang Liu;Weilin Wu;Guannan Chen
Author_Institution :
Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Normal University Fuzhou, 350007, China
Abstract :
Segmentation of the retina vessels plays an important role in detecting earlier diseases, i.e. diabetic and hypertension. These diseases may cause the shape change of the vasculature. Due to the inhomogeneous of the retina image, it´s very difficult to use region static information to get the result. We use a new level set method based on local region cluster information which proves to be well performed the inhomogeneous of the retina image. Experiment shows that our method is more robust to the initial contour C. In the experiment, our method can get a desirable segmentation result in the segmentation of retina images.
Keywords :
"Retina","Image segmentation","Level set","Nonhomogeneous media","Minimization","Mathematical model","Biomedical imaging"
Conference_Titel :
Image and Signal Processing (CISP), 2015 8th International Congress on
DOI :
10.1109/CISP.2015.7407915