Segmentation of MR images using neural nets

A two tier system for MR image segmentation is proposed. The first stage involves probabilistically classifying the pixels of the input image based on second order grey level statistics obtained from the co-occurrence matrix. These probabilities then form the input to a multilayer perceptron, allowing contextual constraints to be applied to local areas of the image improving the spatial coherence of the classification