Retinal Vessel Segmentation Based on Adaptive Random Sampling

Abstract

This paper presents a method for the extraction of blood vessels from fundus images. The proposed method is an unsupervised learning method which can automatically segment retinal blood vessels based on an adaptive random sampling algorithm. This algorithm consists in taking an adequate number of random samples in fundus images, and all the samples are contracted to the position of the blood vessels, then the retinal vessels will be revealed. The basic algorithm framework is presented in this paper and several preliminary experiments validate the feasibility and effectiveness of the proposed method. 

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Cite this paper

@inproceedings{Jouandeau2014RetinalVS, title={Retinal Vessel Segmentation Based on Adaptive Random Sampling}, author={Nicolas Jouandeau and Zhi Yan and Patrick Greussay and Beiji Zou and Yao Xiang}, year={2014} }