The use of image processing techniques in the diagnosis of brain tumors

The current research was conducted with the aim of identifying human brain tumor in MRI medical images using image processing and machine learning techniques. The present study is one of the applied studies in terms of its purpose. In terms of data collection, it is a modeling study, and in terms of data analysis, it was an analytical study. The proposed algorithm for identifying and classifying images related to healthy and cancerous brain are respectively: selection of suitable images, pre-processing of images including removal of image noise, extraction of features from images, selection of features from the output and finally classification of images into two healthy tumor groups. and cancer In this research, we clustered the image based on features using FCM. Images were classified using svm algorithm and tumorous images were identified. The combined algorithm of the three mentioned algorithms has been used to first reduce the noise and then process the data in order to segment the images and diagnose the tumor in them. The results of the study indicate the advantage of the high accuracy of the integrated algorithm in diagnosing and determining the location of the tumor in the scanned image compared to other algorithms.