A note on graph theory techniques for brain tumor detection

Abstract

Brain Tumors are detected in people of all age groups. It leads to various complications that are both physiological and psychological. Graph theory techniques are employed to study both functional and structural behavior of brain networks. In this article we discuss the pertinence of the computation of graph structural parameters and explain how perceptual clustering techniques enable the detection of the low/high grade of tumor and the pace with which it progresses and how Graph cut approaches are exploited to probe vision related factors like similarity and proximity and indicate the possibility of application to stereo, image re-impose, texture concoction and image departmentalization.