# American Institute of Mathematical Sciences

May  2014, 8(2): 459-473. doi: 10.3934/ipi.2014.8.459

## Retinal vessel segmentation using a finite element based binary level set method

 1 Department of Mathematics and Mechanics, University of Science and Technology Beijing (USTB), Beijing, 100083, China 2 Division of Mathematics, University of Dundee, Dundee, DD1 4HN, United Kingdom 3 College of Information Science and Engineering, Ocean University of China, Qingdao, 266071, China 4 College of Marine Life Science, Ocean University of China, Qingdao, 266071, China

Received  July 2012 Revised  October 2013 Published  May 2014

In this paper we combine a few techniques to label blood vessels in the matched filter (MF) response image by using a finite element based binary level set method. An operator-splitting method is applied to numerically solve the Euler-Lagrange equation from minimizing an energy functional. Unlike the traditional MF methods, where a threshold is difficult to be selected, our method can automatically get more precise blood vessel segmentation using an enhanced edge information. In order to demonstrate the good performance, we compare our method with a few other methods when they are applied to a publicly available standard database of coloured images (with manual segmentations available too).
Citation: Zhenlin Guo, Ping Lin, Guangrong Ji, Yangfan Wang. Retinal vessel segmentation using a finite element based binary level set method. Inverse Problems & Imaging, 2014, 8 (2) : 459-473. doi: 10.3934/ipi.2014.8.459
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