MR Image Registration Based on Pulse-Coupled Neural Networks

Authors:
Zhiyong Qiu;Jiyang Dong;Zhong Chen
Affiliations:
Department of Physics, Fujian Engineering Research Center for Solid-State Lighting, Xiamen University, Xiamen, 361005, P.R. China;Department of Physics, Fujian Engineering Research Center for Solid-State Lighting, Xiamen University, Xiamen, 361005, P.R. China;Department of Physics, Fujian Engineering Research Center for Solid-State Lighting, Xiamen University, Xiamen, 361005, P.R. China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

A new algorithm for magnet resonance (MR) image registration is proposed based on a modified Pulse-Coupled Neural Networks (PCNN's). The transformed image and reference image are applied as inputs to two modified networks with the same parameters respectively. Taking advantage of translation, rotation, and distortion invariant characteristics of PCNN's, fired neuron groups of the two networks are acquired correspondingly, then the barycenters of those groups are extracted as characteristic points to attain the registration parameters. Experiment results showed that the proposed algorithm for MR image registration is fast and effective.