Abdominal CT liver parenchyma segmentation based on particle swarm optimization

Abstract

Image segmentation is an important task in the image processing field. Efficient segmentation of images considered important for further object recognition and classification. This paper presents a novel segmentation approach based on Particle Swarm Optimization (PSO) and an adaptive Watershed algorithm. An application of liver CT imaging has been chosen and PSO approach has been applied to segment abdominal CT images. The experimental results show the efficiency of the proposed approach and it obtains overall accuracy 94 % of good liver extraction.