Paper Info
Title
Liver segmentation in MRI images based on whale optimization algorithm.
Abstract
This paper proposes an approach for liver segmentation in MRI images based on Whale optimization algorithm (WOA). It is used to extract the different clusters in the abdominal image to support the segmentation process. A statistical image is prepared to define the potential liver position in the abdominal image. Then, WOA divides the image into a predefined number of clusters. The prepared statistical image is converted into a binary image and multiplied by the image clustered by WOA. This multiplication process removes a great part of other organs from the image. It is followed by some points, picked up by user interaction, representing the required clusters which reside in the area of liver. The morphological operations enhance the initial segmented liver and produces the final image. The proposed approach is tested using a set of 70 MRI images, annotated and approved by radiology specialists. The resulting image is validated using structural similarity index measure (SSIM), similarity index (SI) and other five measures. The overall accuracy of the experimental result showed accuracy of 96.75% using SSIM and 97.5 using SI%.
Year
DOI
Venue
2017
https://doi.org/10.1007/s11042-017-4638-5
Multimedia Tools Appl.
Keywords
Field
DocType
Whale optimizer,Clustering,Segmentation
Computer vision,Scale-space segmentation,Pattern recognition,Image texture,Computer science,Segmentation,Binary image,Segmentation-based object categorization,Image segmentation,Multiplication,Artificial intelligence,Cluster analysis
Journal
Volume
Issue
ISSN
76
23
1380-7501
Citations 
PageRank 
References 
7
0.43
13
Authors
4
Name
Order
Citations
PageRank
Abdalla Mostafa1203.26
Aboul Ella Hassanien21610192.72
Mohamed Houseni370.43
Hesham A. Hefny48320.30