Title :
Ant-based clustering algorithm for magnetic resonance breast image segmentation
Author :
Moftah, Hossam M. ; Hassanien, Aboul Ella ; Alimi, Adel M. ; Karray, Hichem ; Tolba, M.F.
Author_Institution :
Fac. of Comput. & Inf., Beni Suef Univ., Beni Suef, Egypt
Abstract :
This article introduces an improved version of the ant-clustering approach for image segmentation. An application of breast cancer magnetic resonance breas imaging has been chosen and the improved ant-based clustering approach has been applied to see their ability and accuracy to isolate the region of interest in the MRI images. The aim of the proposed ant-based clustering is to identify target objects through an The experimental results obtained, show that the modified ant-based clustering is superior to the classical ant-based clustering and the overall accuracy offered by the improved approach confirm that the effectiveness and performance is 98% in average.
Keywords :
biomedical MRI; gynaecology; image segmentation; medical image processing; optimisation; pattern clustering; MRI images; ant-based clustering algorithm; breast cancer magnetic resonance breast imaging; magnetic resonance breast image segmentation; target objects; Accuracy; Algorithm design and analysis; Clustering algorithms; Image segmentation; Ant colony optimization; Segmentation; clustering; magnetic resonance images;
Conference_Titel :
Hybrid Intelligent Systems (HIS), 2013 13th International Conference on
Conference_Location :
Gammarth
Print_ISBN :
978-1-4799-2438-7
DOI :
10.1109/HIS.2013.6920475
