Optimization neural networks for the segmentation of magnetic resonance images

The application of the Hopfield neural network for the multispectral unsupervised classification of MR images is reported. Winner-take-all neurons were used to obtain a crisp classification map using proton density-weighted and T/sub 2/-weighted images in the head. The preliminary studies indicate that the number of iterations needed to reach 'good' solutions was nearly constant with the number of clusters chosen for the problem.<
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