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Authors
Affiliations
1 Department of Computer Science, Government Arts College, Salem, IN
2 Department of Computer Science, Chikkanna Government Arts College, IN
Source
ICTACT Journal on Image and Video Processing, Vol 6, No 1 (2015), Pagination: 1096-1103
Abstract
Diagnostic imaging is invaluable. Magnetic Resonance Imaging (MRI), digital mammography, Computed Tomography (CT), and others ensure effective noninvasive mapping of a subject's anatomy, and increased normal and diseased anatomy knowledge for medical research in addition to being a critical component in diagnosis and treatment. In this work various feature selection algorithms are investigated and a Swarm Intelligence Algorithm based on Bacterial Foraging is proposed. Features are extracted using wavelet and Gray-Level Co-occurrence Matrix (GLCM). The obtained features are fused using Median Absolute Deviation (MAD) after normalization and the feature selection techniques investigated. Results obtained show the improved performance of Bacterial Foraging based feature selection for different classifiers.
Keywords
Computed Tomography (CT), Wavelet, Gray-Level Co-Occurrence Matrix (GLCM), Median Absolute Deviation (MAD), Correlation Based Feature Selection (CFS), Bacterial Foraging Optimization (BFO).
