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Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 9 | Page No.: 1733-1739
DOI: 10.3923/itj.2011.1733.1739
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Medical Image Registration using Cascaded Pulse Coupled Neural Networks

Changtao He, Fangnian Lang and Hongliang Li

This study presented a novel image registration algorithm for Magnet Resonance Image (MRI) using cascaded Pulse Coupled Neural Networks (PCNNs). Firstly, the two unregistrated images’ barycenters and foveation points are extracted respectively. Next, obtaining some clustering centers of the extracted foveations via fuzzy C-Means clustering (FCM) algorithm. Finally, using barycenter as coordinate origin and the corresponding clustering centers of foveations as characteristics to build coordinate system and attain the correlative registration parameters. The experimental results show that registration accuracy of the proposed algorithm is 95.7%. Meanwhile, it is robust and effective for MR image registration.
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  •    Medical Image Fusion with Adaptive Region-based Direction Feature
  •    Software Refactoring: Solving the Time-Dependent Schrodinger Equation via Fast Fourier Transforms and Parallel Programming
  •    Automatic Panorama Creation using Multi-row Images
  •    New Fully Automatic Fast Registration Method for 2D Computed Tomography Images
How to cite this article:

Changtao He, Fangnian Lang and Hongliang Li, 2011. Medical Image Registration using Cascaded Pulse Coupled Neural Networks. Information Technology Journal, 10: 1733-1739.

DOI: 10.3923/itj.2011.1733.1739






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