Abstract
Diagnosing brain tumor in present era through digital techniques need serious attention as the number of patients are increasing in an awkward manner. Magnetic Resonance Imaging is the tool that is used for detection of brain tumors. This paper is classified in two phases i.e. normal and abnormal brain images. Then, Feature selection and classification are applied on the given data set. Classification on given data set is done through K- Nearest Neighbor. In the given study, we have taken normal and abnormal samples from Nishtar Medical hospital, Multan. In order to classify brain images, first it needs to pre-process through skull stripping technique then the proposed algorithm is followed. Algorithm involves feature extraction through GLCM and feature selection through ACO. Results have proved its efficiency level up-to 88%.
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