An Elitist Approach to Analyze Breast Cancer Histology Slides Using Genetic Algorithm
摘要
This work proposes an image segmentation approach using an elitist genetic algorithm. The proposed approach is implemented on breast cancer histology slides. The suggested approach optimizes the Davies–Bouldin index and Silhouette Coefficient to get the optimal clustering outcome. It additionally addresses the reliance on the initial cluster centers. Nevertheless, the number of clusters in an image cannot be automatically determined by the proposed approach. The experimental outcomes are promising, endorsing the applicability of the suggested approach in real-world applications. The analysis also considers how altering the number of clusters affects the optimal outcome.