Deep learning to combat knee osteoarthritis and severity assessment by using CNN-based classification.

Autor: Rani S; Department of Computer Science and Engineering, Uttaranchal Institute of Technology (UIT), Uttaranchal University, Dehradun 248007, Uttarakhand, India., Memoria M; Department of Computer Science and Engineering, Uttaranchal Institute of Technology (UIT), Uttaranchal University, Dehradun 248007, Uttarakhand, India., Almogren A; Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, 11633, Saudi Arabia., Bharany S; Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140401, India. salil.bharany@gmail.com., Joshi K; Department of Computer Science and Engineering, Uttaranchal Institute of Technology (UIT), Uttaranchal University, Dehradun 248007, Uttarakhand, India., Altameem A; Department of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh, 11543, Saudi Arabia., Rehman AU; School of Computing, Gachon University, Seongnam-si, 13120, Republic of Korea. 202411144@gachon.ac.kr., Hamam H; School of Electrical Engineering, University of Johannesburg, Johannesburg, 2006, South Africa.; Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.; Hodmas University College, Taleh Area, Mogadishu, Banadir, 521376, Somalia.; Bridges for Academic Excellence - Spectrum, Tunis Centre-Ville, 1002, Tunisia.
Jazyk: angličtina
Zdroj: BMC musculoskeletal disorders [BMC Musculoskelet Disord] 2024 Oct 16; Vol. 25 (1), pp. 817. Date of Electronic Publication: 2024 Oct 16.
DOI: 10.1186/s12891-024-07942-9
Abstrakt: Background: In today's digital age, various diseases drastically reduce people's quality of life. Arthritis is one amongst the most common and debilitating maladies. Osteoarthritis affects several joints, including the hands, knees, spine, and hips. This study focuses on the medical disorder underlying Knee Osteoarthritis (KOA) which severely impairs people's quality of life. KOA is characterised by restricted mobility, stiffness, and terrible pain and can be caused by a range of factors such as ageing, obesity, and traumas. This degenerative disorder leads to progressive wear and tear of the knee joint.
Methods: To combat arthritis in the kneecap, this study employs a 12-layer Convolutional Neural Network (CNN) to reach deep learning capabilities. A collection of data from the Osteoarthritis Initiative (OAI) is used to classify KOA. Through the use of medical image processing; the study ascertains whether an individual has this ailment. A sophisticated CNN architecture created especially for binary classification and KOA severity utilising deep learning algorithms is the main component of this work.
Results: The cross-entropy loss function is an important component of the model's laborious design that classifies data into two groups. The remaining section uses the Kellgren-Lawrence (KL) grade to classify the disease's severity. In the binary classification, the proposed algorithm outperforms previous methods with an accuracy rate of 92.3%, and in the multiclassification, its accuracy rate is 78.4% which is superior to the previous findings.
Conclusion: Looking ahead, the research broadens the scope of this work by gathering information from various sources and using these methods on a wider range of datasets and situations. The potential for major advancements in the field of osteoarthritis detection and classification is highlighted by this forward-looking approach. Furthermore, this method reduces the intervention of medical practitioners and ultimately results in accurate diagnosis.
Clinical Trial Number: Not applicable.
(© 2024. The Author(s).)
Databáze: MEDLINE
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