Paper Info
Title
Antlion Optimization Based Segmentation for MRI Liver Images.
Abstract
This paper proposes an approach for liver segmentation, depending on Antlion optimization algorithm. It is used as a clustering technique to accomplish the segmentation process in MRI images. Antlion optimization algorithm is combined with a statistical image of liver to segment the whole liver. The segmented region of liver is improved using some morphological operations. Then, mean shift clustering technique divides the segmented liver into a number of regions of interest (ROIs). Starting with Antlion algorithm, it calculates the values of different clusters in the image. A statistical image of liver is used to get the potential region that liver might exist in. Some pixels representing the required clusters are picked up to get the initial segmented liver. Then the segmented liver is enhanced using morphological operations. Finally, mean shift clustering technique divides the liver into different regions of interest. A set of 70 MRI images, was used to segment the liver and test the proposed approach. Structural Similarity index (SSIM) validates the success of the approach. The experimental results showed that the overall accuracy of the proposed approach, results in 94.49% accuracy.
Year
DOI
Venue
2016
10.1007/978-3-319-48490-7_31
GENETIC AND EVOLUTIONARY COMPUTING
Keywords
Field
DocType
Antlion optimization,Mean shift clustering,Segmentation
Whole liver,Pattern recognition,Computer science,Segmentation,Optimization algorithm,Pixel,Artificial intelligence,Mean-shift,Cluster analysis,Antlion,Machine learning
Conference
Volume
ISSN
Citations 
536
2194-5357
0
PageRank 
References 
Authors
0.34
2
6
Name
Order
Citations
PageRank
Abdalla Mostafa1203.26
Mohamed Houseni200.34
Naglaa Allam300.34
Aboul Ella Hassanien41610192.72
Hesham A. Hefny58320.30
Tsai Pei-wei612715.88