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In this paper a new framework is suggested for segmentation of medical images (MRI) using hybrid optimization technique. This frame work includes de-nosing as image enhancement technique using discrete wavelet transform and initial segmentation is obtained by Hidden Markov random field model along with Kmeans clustering to get Maximum a posterior values (thresholds). The optimal solution for these thresholds is achieved by incorporating a new concept of Adjusted Ant colony optimization. Finally a fine segmentation is obtained. The algorithm is tested for some of the medical images and for validation purpose various parameters like accuracy, sensitivity, dice, Jaccard, are obtained.

A Hybrid Framework for Segmentation of MR Medical Images Using Adjusted Ant Colony Optimization