Optimizing Brain Tumor Classification: A Comparative Analysis of Nature Inspired Algorithms with GLCM Features
selvan P,
Kavitha A
Abstract:Advancements in medical imaging have led to an increasing demand for accurate and efficient methods of brain tumor classification. This study delves into the realm of nature-inspired optimization algorithms, with a focus on their application in the field of medical image analysis. We examine the performance of three distinct algorithms: Firefly, Cat Swarm Optimization (CSO), and Artificial Fish Swarm Optimization Algorithm (AFSA), in the context of brain tumor classification. Among these, CSO emerges as the st… Show more
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