Adjustment of active contour parameters in Brain MRI segmentation using evolution strategies

In this paper, we propose an approach for segmentation of Brain Magnetic Resonance Images (MRI) using an active contour model. We adopted a Greedy Algorithm which is a simple and an effective method. However it requires an adjustment of functional energy parameters. To overcome this disadvantage we propose a hybridization with optimization method. We apply the Evolutionary Strategy (ES) which proved its success in numerical optimization. Experimental results on brain MRI images reveal a clear efficiency of this hybridization.