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Automatic Image Segmentation Algorithm Based on PCNN and Fuzzy Mutual Information

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3 Author(s)
Zhiheng Xiao ; Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China ; Jun Shi ; Qiang Chang

The pulse coupled neural network (PCNN) algorithm has been effectively used in image segmentation. In this paper, we proposed a new image auto-segmentation algorithm based on PCNN and fuzzy mutual information (FMI). The image was firstly segmented by PCNN, and then FMI was used as the optimization criterion to automatically stop the segmentation with the optimal result. Different images were segmented by max-FMI PCNN, Otsu segmentation algorithm and max-entropy PCNN to evaluate the segmentation accuracy. The experimental results demonstrated that the CT and ultrasound images could be well segmented by the proposed algorithm with strong robustness against noise. The results suggest that the proposed algorithm can be used for medical image segmentation.

Published in:

Computer and Information Technology, 2009. CIT '09. Ninth IEEE International Conference on  (Volume:1 )

Date of Conference:

11-14 Oct. 2009