Exploring functional connectivity networks in fMRI data using clustering analysis
BI'11 Proceedings of the 2011 international conference on Brain informatics
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Accurate segmentation of magnetic resonance images(MRI) corrupted by intensity in homogeneity is a challenging problem and has received an enormous amount of attention lately. On the basis of the local image model, we propose a different segmentation method for MR brain images without estimation and correction for intensity heterogeneity. Firstly, we obtain clustering context which size is optimized by a minimum entropy criterion. Then, Each context is segmented by Affinity Propagation(AP) algorithm. The proposed methodology has been evaluated for simulated images and shown the better results.