Segmentation of MR images using neural nets

摘要

A two tier system for magnetic resonance (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 multi-layer perceptron, allowing contextual constraints to be applied to local areas of the image thereby improving the spatial coherence of the classification.