Medical image fusion based on pulse coupled neural networks and multi-feature fuzzy clustering
- 1 School of IoT Engineering, Jiangnan University, Wuxi, China
- 2 School of IoT Engineering, Jiangnan University, Wuxi, China
Abstract
Medical image fusion plays an important role in clinical applications such as image-guided surgery, image-guided radiotherapy, noninvasive diagnosis, and treatment planning. In order to retain useful information and get more reliable results, a novel medical image fusion algorithm based on pulse coupled neural networks (PCNN) and multi-feature fuzzy clustering is proposed, which makes use of the multi-feature of image and combines the advantages of the local entropy and variance of local entropy based PCNN. The results of experiments indicate that the proposed image fusion method can better preserve the image de tails and robustness and significantly improve the image visual effect than the other fusion methods with less information distortion.
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