Classification of Human Brain Tumors from Mri Using K-nn Algorithm
نویسنده
چکیده
Tumor classification and segmentation of brain magnetic resonance imaging (MRI) image data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and in many cases, similarity between tumor and normal tissue. Brain imaging segmentation is a complex and challenging part in the Medical Image Processing. This research deals with new approaches for brain Tumor detection using K-NN Algorithm as a classifier and Kmeans clustering as segmentation. It aims to develop and effective algorithm for the segmentation of Brain MRI images. The imaging modalities most often used for diagnosis of brain diseases is magnetic resonance imaging (MRI) and computerized tomography (CT). MRI or CT scans show a brain tumor, if one is present, in more than 95% of cases. KeywordsCBIR, Feature Extraction and Reduction, K-NN Algorithm, Jolliffe’s B4 Method.
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