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A fusion technique for medical image segmentation

This work provides a fusion approach for medical image segmentation. The fusion approach is proposed based on a Global Minimization by active contour and spatial fuzzy clustering model. The global minimization of the active contour model is based on the unification of image segmentation and image denoising tasks. The idea is to minimizing the energy level that unified way to perform image denoising and segmentation. In second stage, Spatial Fuzzy C Means Clustering (SFCM) is used to refine the final segmentation result. The experimental results show that the new proposed algorithm can provide close, smooth and accurate results based on, Energy, Mutual Information and Elapsed Time.