Ant Colony optimization algorithm for breast cancer cells classification

Ant colony optimization (ACO) is a bio-inspired technique formalized into a meta-heuristic for combinatorial optimization problems. In this work, the ACO-Otsu segmentation method, based on ACO algorithm and Otsu´s method as a fitness function, is applied in classification and detection of breast cancer cells. Subsequently, this method is compared with the Otsu´s standard method. The experiments show the performance of this probabilistic search approach in such type of problems.