An optimized technique for brain tumor classification and detection with radiation dosage calculation in MR image

Abstract

The tumor cell leads brain to abnormal growth birth. The Brain Tumors (BT) leads to damage or affected brain if it is not predicted early stage and rectified properly with proper treatment. The proper treatment as advised by the physician need to be followed based on the size of the tumor and its position. The accurate finding of tumor position and size is the difficult task. In recent years to structures of the body in internal position had seen detailed, the Magnetic Resonance (MR) technique if the radiology used in medical imaging. This paper describes a novel approach for BT MLTS-HSO segmentation and extracts the features then classified with different classifiers (KNN, DSVM, NB, and RBFN) for MR BT images. The present approach is SVM, NN, and ANFIS where the seed point is selected on a scale based and detected the tumor region and also compute the performance metrics and radiation dosage. Thus the proposed system is the ability of the calculate size and position of the tumor. It has more accurate prediction of the required surgery and other therapy procedures.