Brain MRI Image Segmentation Using Ant Colony Algorithm

Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique. In brain MRI analysis, image segmentation provides valuable information for understanding the anatomical structures of the brain. Currently, segmentation is typically performed by human experts, which is the conventional approach. However, due to challenges such as the complex anatomical shapes of tissues and noise captured by the imaging device, this process is not easily achievable. In this research, a method for image segmentation using the Ant Colony Optimization (ACO) algorithm is proposed. The ACO algorithm is combined with the k-means algorithm to optimally select cluster centers. Subsequently, the performance of the proposed segmentation method is evaluated and compared with existing approaches. The proposed method is simulated in MATLAB software. The accuracy of the proposed algorithm is ۹۹.۵%, which is higher than that of existing methods.

کلیدواژه ها:

Image Segmentation ، Ant Colony Optimization ، k-means Algorithm