Abstract

The level of accuracy needed to identify the type of tumor using MRI data is necessary to choose the best method for medical care. The K-Nearest Neighbor approach, a fundamental scientific application and image classification technique, can be used to computationally analyze MRI results. The objective of the tumor classification system is to identify the tumor. The only information used to analyze data for this type of system comes from the MRI's axial portion, which are divided into three categories they are: oligodendroglioma, glioblastoma, and astrocyte. Basic image processing techniques, such as image enhancement, image biniarization, morphological image and watershed are used to identify the tumor region. Tumor categorization achieved findings of 89.5 percent, which may provide more precise and in-depth information about tumor identification.