Document Type : Primary Research paper
Authors
1
Assistant Professor, PG & Research Dept. Computer Science, Arignar Anna Govt. Arts College for Women , Walajapet - 632 513 , Ranipet Dist. , Tamil Nadu , India.
2
Associate Professor, Department of Computer Science and Engineering, CMR Technical Campus, Kandlakoya (V), Medchal Road, Hyderabad 501401, Telangana,India.
3
Assistant Professor, Department of Mathematics, Silapathar College, Dhemaji Assam- 787059.
4
Assistant Professor, Computer Science & Engineering, Avanthi Institute of Engineering and Technology, Gunthapally, Abdullahpurmet Mandal, Telangana-501512.
5
Professor, Department of Computer Science & Engineering, Dr.Samuel George Institute of Engineering & Technology, Markapur, Prakasam Dt, Andhra Pradesh, 523316.
6
Associate professor, Mathematics, Sri Eshwar College of Engineering, Coimbatore- 641202.
Abstract
Graph theory is a branch of discrete mathematics that deals with the connections among
fundamental results in other areas of pure mathematics. The aim of this study is two folds:
first, to understand the basic notion of graph theory and second, to emphasis the
significance of graph theory through a real-time application used as a representational
form and characterization of brain connectivity network, as is machine learning for
classifying groups depending on the features extracted from images. This application uses
different techniques including preprocessing, correlations, features or algorithms. This
paper illustrates an automatic tool to perform a standard process using images of the
Magnetic Resonance Imaging (MRI) machine. The process includes pre-processing,
building the graph per subject with different correlations, atlas, relevant feature extraction
according to the literature, and finally providing a set of machine learning algorithms that
can produce analyzable results for physicians or specialists. Further, to demonstrate the
importance of graph theory, this article addresses the most common applications for graph
theory in various fields. This paper also presents a survey on the graph theory challenges
relevant to their approaches and techniques.
Keywords
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