Brain Tumor Segmentation Using Fuzzy C Means With Ant Colony Optimization Algorithm
نویسنده
چکیده
In computer vision, image segmentation is an important problem and plays vital role in medical imaging. Analysis and diagnosis of tumor in MRI brain image involves segmentation as very essential steep. It separates the region of interest objects from the background and the other objects. Several approaches are used for MRI brain tumor segmentation. Fuzzy C Means (FCM) is most widely used fuzzy clustering algorithm. The accuracy of this algorithm for segmentation is not efficient due to limitation in initialization. In this paper, ant colony algorithm with min max ant system is used to improve the segmentation accuracy by maximum 32 % and reduce the computational time by maximum 2.5 times respectively. Keyword — Magnetic Resonance Image (MRI), Brain Tumor segmentation, Fuzzy Interference System (FIS), Fuzzy C Means (FCM), Ant Colony Algorithm (ACA), Min Max Ant System (MMAS).
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