Detection and Analysis of Brain Tumors on the Basis of their Area and Density by Segmentation

Abstract

Brain Cancer is recognized to be a deadly and most prevalent disease around the globe. The prime step in curing brain tumor is its detection, as it is required for diagnosis of this disease. With the help of Computer-Aided Diagnosis (CAD), the detection and diagnosis of brain tumors can be automated. The major issues that are encountered in designing these automated diagnosis systems are efficiency and accuracy.  The tumors in Brain Magnetic Resonance imaging (MRI) may be visible clearly; however, the quantification of the tumor affected sites is required. In this regard, computerized image processing methods can provide great assistance. In this paper, the brain tumors have been identified and classified in two major types i.e., malignant and benign tumors, depending upon the texture and shape of the MRI image tumor. Four steps have been followed including preprocessing, skull stripping, segmentation and feature extraction. MATLAB image processing toolbox has been utilized to implement the approach. The results can conclude that shape features and texture of brain tumor in MRI images can be used for their classification with great degree of accuracy.