Classification of brain tumor using devernay sub-pixel edge detection and k-nearest neighbours methodology

Any disease can be treated only once it is imaged, detected and classified. This paper proposes a set of algorithms for classification of a brain tumor with better accuracy and efficiency. The proposal uses a JPEG format of the DICOM image fed into three stages namely pre-processing, segmentation using sub-pixel edge detection method and using the nearest neighbor methodology for the detection and differentiation of benign and malignant tumors.