Graph Based Brain Network Structure and Brain MRI Segmentation Techniques
Mamatha S K1, Krishnappa H K2

1Mamatha S K, Assistant Professor, CSE Department Dr.AIT, Bangalore, India.
2Krishnappa H K, Associate Professor, 2CSE Department RVCE, Bangalore, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 2845-2854 | Volume-8 Issue-6, March 2020. | Retrieval Number: E6840018520/2020©BEIESP | DOI: 10.35940/ijrte.E6840.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Graph based representation of medical images is very challenging task due to complexity of various images taken using different techniques like MRI, Ultrasound, CT scan and PET scan. Graph theory provides simplified notations and tools in order to representation Brain network structure. The brain network structure helps to analyze and detect brain tumor because it is structurally and functionally organized complex system. Brain network structure and functional analysis using graph based techniques have been successfully used in various types images and medical data analysis. Simplified representation of brain structure plays a crucial role in analysis and detection of brain related diseases. Because various kinds brain tumor types allows to have different images and brain tumor analysis is one of the most significant challenges. This paper also represents graph theory based brain tumor detection and classification steps using hybrid Fuzzy C-Means technique. Segmentation error may increase due to presence of noise, intensity variations, interclass values in manual segmentation. To avoid this, use automatic segmentation which gives better results for clinical analysis of MRI images. In this paper different types brain tumors, Graph based analysis of complex Brain Structure, various brain tumor segmentation and detection techniques using MRI and its merits and demerits are surveyed and summarized. We also discussed future research directions in analysis of MR Images and some challenging issues of brain tumor evolving in medical research field.
Keywords: Graph theory, Magnetic Resonance Images, Brain Network Structure, Fuzzy C-Means.
Scope of the Article: Software safety systems.