Abstract
In this paper, a new multi-modality medical image fusion algorithm based on pulse-coupled neural networks (PCNN) is presented. Firstly a multi-scale decomposition on each source image is performed, and then the PCNN is used to combine these decomposition coefficients. Finally an inverse multi-scale transform is taken upon the new fused coefficients to reconstruct fusion image. The new algorithm utilizes the global feature of source images because the PCNN has the global couple and pulse synchronization characteristics. Series of experiments are performed about multi-modality medical images fusion such as CT/MRI, CT/SPECT, MRI/PET, etc. The experimental results show that the new algorithm is very effective and provides a good performance in fusing multi-modality medical images.
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