Open AccessAssessment of Joint Space in Knee Osteoarthritis using Particle Swarm Optimization Technique
Author(s) -
Vijayakumari G*,
Ganga Holi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c4246.119119
Subject(s) - osteoarthritis , thresholding , particle swarm optimization , cartilage , knee joint , preprocessor , joint (building) , segmentation , medicine , computer science , orthodontics , artificial intelligence , surgery , anatomy , pathology , algorithm , engineering , structural engineering , alternative medicine , image (mathematics)
Osteoarthritis (OA) is one of the most common joint disorder which is debility seen in elderly & overweight people which affects the cartilage of bone joints like knee, feet, hip, and spine. In OA usually, cartilage is ruptured due to the kneading of bones with each other which will end up causing severe pain. In this condition, it is necessary to analyze the severity of OA which involves various medical imaging and clinical examination techniques. In this paper, automated analysis and detection of OA are proposed by calculating the thickness of cartilage which also helps to effectively detect and analyze the abnormalities in bone structures. Where we have considered various knee X-ray images. Initially, preprocessing and noise removal is performed. Further by implementing Particle Swarm Optimization (PSO) segmentation and thresholding, the specified knee region is cropped and analyzed to calculate the thickness of cartilage to detect the presence of OA.