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2019 | OriginalPaper | Chapter

Comparison of Particle Swarm Optimization and Weighted Artificial Bee Colony Techniques in Classification of Dementia Using MRI Images

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Abstract

Numerous soft computing techniques are used nowadays to analyze medical images, and diagnosis of disease is computerized. This paper compares the performance of Weighted Artificial Bee Colony and Particle Swarm Optimization in the diagnosis of dementia using MRI images. For analysis, cross-sectional MRI of 235 subjects collected from OASIS is used. By adjusting the weights for both optimization techniques in a proper manner, optimized results can be reached. These techniques classify the cross-sectional image into three categories and give almost equal Goodness Detection Ratio of 78% along with different regression ratios.

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Metadata
Title
Comparison of Particle Swarm Optimization and Weighted Artificial Bee Colony Techniques in Classification of Dementia Using MRI Images
Authors
N. Bharanidharan
Harikumar Rajaguru
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-00665-5_95