Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images
Joint Authors
Gopalakrishnan, Ravichandran C.
Kuppusamy, Veerakumar
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-26
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Lung cancer is becoming a threat to mankind.
Applying machine learning algorithms for detection and segmentation of irregular shaped lung nodules remains a remarkable milestone in CT scan image analysis research.
In this paper, we apply ACO algorithm for lung nodule detection.
We have compared the performance against three other algorithms, namely, Otsu algorithm, watershed algorithm, and global region based segmentation.
In addition, we suggest a novel approach which involves variations of ACO, namely, refined ACO, logical ACO, and variant ACO.
Variant ACO shows better reduction in false positives.
In addition we propose black circular neighborhood approach to detect nodule centers from the edge detected image.
Genetic algorithm based clustering is performed to cluster the nodules based on intensity, shape, and size.
The performance of the overall approach is compared with hierarchical clustering to establish the improvisation in the proposed approach.
American Psychological Association (APA)
Gopalakrishnan, Ravichandran C.& Kuppusamy, Veerakumar. 2014. Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1016826
Modern Language Association (MLA)
Gopalakrishnan, Ravichandran C.& Kuppusamy, Veerakumar. Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-16.
https://search.emarefa.net/detail/BIM-1016826
American Medical Association (AMA)
Gopalakrishnan, Ravichandran C.& Kuppusamy, Veerakumar. Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1016826
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016826