Extraction of brain tumors from MRI images with artificial bee colony based segmentation methodology

Abstract

Image segmentation plays significant role in medical applications to extract or detect suspicious regions. In this paper, a new image segmentation methodology based on artificial bee colony algorithm (ABC) is proposed to extract brain tumors from magnetic reasoning imaging (MRI), one of the most useful tools used for diagnosing and treating medical cases. The proposed methodology comprises three phases: enhancement of the original MRI image (pre-processing), segmentation with the ABC based image clustering method (processing), and extraction of brain tumors (post-processing). The proposed methodology is compared and analyzed on totally 9 MRI images shooting in different positions from a patient with the methodologies based on K-means, Fuzzy C-means and genetic algorithms. It is observed from the experimental studies that the segmentation process with the ABC algorithm obtains both visually and numerically best results.