A GRAPH THEORETICAL APPROACH TO IDENTIFY MORPHOLOGICAL VARIATIONS IN HARD AND SOFT TISSUES OF THE FACE IN CLASS 1 AND CLASS 2 MALOCCLUSION
Journal: International Education and Research Journal (Vol.3, No. 3)Publication Date: 2017-03-15
Authors : P.Lalitha Gayathri.M Dr.A.V.Arun;
Page : 127-129
Keywords : ;
Abstract
In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. Network analysis has been applied recently to orthodontics to detect and visualize the most interconnected clinical, radiographic, and functional data pertaining to the orofacial system. In particular, by considering phenotypic, functional, and radiographic characteristics it has been shown that different kinds of dentofacial malocclusions correspond to different network structures. During the diagnostic process to establish the objectives, strategies, priorities and sequences of treatment, the orthodontist has to identify and locate the critical points of malocclusion.
The craniofacial region can be regarded as a complex system that grows and remodels itself following an intricate network of auxologic forces, distortive processes and/or compensatory mechanisms. The aim of this study is to show how ‘‘network thinking'' and network modelling leads to a systemic analysis of standard diagnostic data under a different perspective. This study was undertaken to determine whether graphically significant differences exist in facial skeletal patterns among groups of cases presenting ANGLE CLASS I and CLASS II malocclusions. Class I subjects exhibited few highly connected orthodontic features (hubs), while Class II patients showed a more compact network structure characterized by strong co-occurrence of normal and abnormal clinical, functional, and radiological features. The topology of the dentofacial system obtained by network analysis could allow orthodontists to visually evaluate and anticipate the co-occurrence of auxological anomalies during individual craniofacial growth and possibly localize reactive sites for a therapeutic approach to malocclusion.
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