Paper Title
Liver Image Segmentation Using Ant Colony Based K-Means Clustering And Level Sets

Image Segmentation is important problem in medical image processing fields. Segmentation of liver remains a challenging task in clinical applications due to high inter-patient variability in size, shape, volume and pathologies. In this paper, we proposed liver image segmentation based on Ant colony Optimization based K-means Clustering and levels sets. The MATLAB is used as a tool for performing this study. The ACO is used to optimize the results of K-Means Clustering algorithm. An Abdominal CT image is used to perform the segmentation process and obtain the results. Keywords - Ant Colony Optimization, K-Means Clustering, Level Set Segmentation, Liver Segmentation.