Paper Title :Severity of Osteoarthritis in the Knee Using a Multi-Scale Deep Convolutional Neural Network and Improved X-Ray Images

Author :Madhavi Mahajan, Gitanjali Mate, Pragati Mahajan, Prajwal Janbandhu, Rutuja Shinde

Article Citation :Madhavi Mahajan ,Gitanjali Mate ,Pragati Mahajan ,Prajwal Janbandhu ,Rutuja Shinde , (2023 ) " Severity of Osteoarthritis in the Knee Using a Multi-Scale Deep Convolutional Neural Network and Improved X-Ray Images " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 87-91, Volume-11,Issue-4

Abstract : Osteoarthritis (OA) is an extensive degenerative joint illness characterized by changes in bone structure and cartilage degradation. Osteoarthritis (OA) is among the most common forms of arthritis, affecting millions of lives worldwide. The proposed method is a deep learning-based framework that automatically assesses the severity of knee OA through the use of Kellgren and Lawrence grade (KL grade) classification using knee X-rays. We use CNN models to predict severity. The scarcity of datasets causes delays, in detecting osteoarthritis in its early stages. To address this limitation, we aim to increase the dataset and enhance the X-ray images to detect the severity as early as possible. For successful outcomes, the suggested approach takes into account several notable factors, such as jointspace narrowing, osteophyte production, and bone deformation over time. This shows promise in improving diagnostic precision, enabling early treatments, and offering customized therapies for OA victims. Keywords - Knee Osteoarthritis, X-Ray, Deep Learning, KL-Grade

Type : Research paper

Published : Volume-11,Issue-4

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