Cardiac image segmentation using Simulated Genetic algorithm

Cardiac Image Segmentation poses many challenges arising from the large variation between different sequences of images. As we know that Segmentation of moving objects in image sequences is more difficult. In the present paper we use Simulated Genetic Algorithm for Cardiac Image Segmentation to deal with these challenges. We propose an algorithm for segmentation of medical image sequences based on Simulated Genetic Algorithm which uses K-mean clustering in the feature vector space. We use two-dimensional feature vector for clustering in the feature space. Experiments on Cardiac images have given the satisfactory results.