关键词: 脉冲耦合神经网络（PCNN）, 血管分割, 视网膜, 分布式遗传算法（DGA）, 参数寻优

Abstract: A new blood vessels automatic detection method is proposed to diagnose fundus disease. In preprocessing, Contrast Limited Adaptive Histogram Equalization（CLAHE） and two-dimensional Gaussian matched filtering are adopted to improve the contrast between blood vessels and background. Then Adaptive Distributed Genetic Algorithm（ADGA） is used to search the best parameters and the blood vessel network is segmented by Pulse Coupled Neural Network（PCNN）. Finally, the final blood vessels detection result is obtained via post processing including area filtering and section connectivity filtering. The experiments implemented on the public STARE database indicate that the method has relatively higher robustness, effectiveness and reliability comparing with the traditional distributed genetic algorithm because of the average accuracy which is increased from 0. 929?3 to 0. 945?4.

Key words: Pulse Coupled Neural Network（PCNN）, blood vessels segmentation, retina, Distributed Genetic Algorithm（DGA）, parameter optimization