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Simultaneous registration and tissue classification using clustering algorithms
By: Bazin, P.-L.; Pham, D.L.;
2006 / IEEE / 0-7803-9576-X
This item was taken from the IEEE Conference ' Simultaneous registration and tissue classification using clustering algorithms ' We describe a novel approach for performing registration and tissue classification of multichannel medical images. Rather than perform a two-step process comprised of a registration step followed by a tissue classification step, the two objectives are accomplished simultaneously using a single algorithm. The new algorithm is based on minimizing a fuzzy C-means clustering energy functional with respect to not only the cluster centers and membership functions, but the transformation parameters as well. The advantage of this simultaneous approach is that both the registration and segmentation now optimize the same cost functional. This approach also allows the registration of more than two images to be easily accommodated. The method is evaluated using both real and simulated magnetic resonance images of the brain.
Fuzzy Set Theory
Medical Image Processing
Multichannel Medical Images
Fuzzy C-means Clustering Energy Functional Minimisation
Magnetic Resonance Images
Magnetic Resonance Imaging