Adaptive particle swarm optimization approach for CT Liver Parenchyma segmentation

Citation:
Sayed, G. I., and A. E. Hassanien, "Adaptive particle swarm optimization approach for CT Liver Parenchyma segmentation", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer, Beni Suef University, Beni Suef, Egypt , Nov. 28-30, 2015.

Date Presented:

Nov. 28-30

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.