Apparent Diagnosis of Periapical Lesions by Particle Swarm Optimization Algorithm
Journal Title: Scholars Journal of Applied Medical Sciences - Year 2016, Vol 4, Issue 9
Abstract
Diagnosis of periapical lesions with no human intervention is discussed in this study. Particle swarm optimization, in principle, is a computing volutionary technique and an optimization population-based method. The purpose of this paper is to diagnose periapical lesions with processing image using particle swarm optimization(PSO)algorithm in the X-Ray Digital (XRD) images that facilitate conducting a more accurate diagnosis. This algorithm is based on examination of the color changes around the tooth roots in the XRD images. The color of the periapical lesions around unhealthy tooth root is darker(Lucent)compared with that of the healthy tooth root (Lucent).The difference between this study and previous ones is computation of the color changes by image processing algorithm for diagnosis of the periapical lesions. Methodology of this algorithm on XRD image is to investigate the color changes around tooth root and to show the lesion existence. After running the algorithm, if the lesion is apical root around, PSO algorithm can recognize periapical lesios and identify its location. This algorithm provides useful and successful results for the presented tests and experiments. Using this algorithm, it is possible to save time, reduce errors, and have a more accurate diagnosis. Among the potential applications of this algorithm is to intelligently help dentist robots, which will be used in the future. Keywords: Particle Swarm Optimization Algorithm, Periapical Lesions, Image Processing
Authors and Affiliations
Sirous Risbaf Fakour, Mohammad Naebi, Eshaghali Saberi, Ahmad Naebi, Somayeh Hosseini Tabatabaei, Nasim Davtalab Behnam, Hamideh Kadeh, Vida Maserat, Ali Mohsenpour, Nazanin Kamyab, Sara Pourabbas Kheiralddin
Keywords
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