Knee osteoarthritis grading using deep learning classifier
This project is a Deep Learning Model research project for academic purpose. Knee osteoarthritis (OA) is a prevalent degenerative joint disorder affecting millions worldwide, leading to pain, impaired mobility, and diminished quality of life. Accurate grading of OA severity is crucial for effective...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/6975/ http://eprints.utar.edu.my/6975/1/fyp_CS_2024_NJ.pdf |
| _version_ | 1848886816572178432 |
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| author | Ng, Jevyline |
| author_facet | Ng, Jevyline |
| author_sort | Ng, Jevyline |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | This project is a Deep Learning Model research project for academic purpose. Knee osteoarthritis (OA) is a prevalent degenerative joint disorder affecting millions worldwide, leading to pain, impaired mobility, and diminished quality of life. Accurate grading of OA severity is crucial for effective clinical management, yet it remains a challenging task prone to subjectivity and inter-observer variability. In this study, we propose a novel approach utilizing deep learning classifiers to automate the grading process of knee OA based on the Kellgren Lawrence grading system. Through the development and evaluation of multiple deep learning models, we aim to provide a robust and reliable tool for clinicians to objectively assess OA severity from X-ray images. Our methodology involves preprocessing of X-ray images, followed by feature extraction and classification using convolutional neural networks (CNNs). The performance of each model is assessed through rigorous validation on a diverse dataset of knee X-ray images annotated with ground truth Kellgren Lawrence grades. |
| first_indexed | 2025-11-15T19:44:30Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-6975 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:44:30Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-69752025-02-27T07:06:24Z Knee osteoarthritis grading using deep learning classifier Ng, Jevyline R Medicine (General) RB Pathology T Technology (General) TD Environmental technology. Sanitary engineering This project is a Deep Learning Model research project for academic purpose. Knee osteoarthritis (OA) is a prevalent degenerative joint disorder affecting millions worldwide, leading to pain, impaired mobility, and diminished quality of life. Accurate grading of OA severity is crucial for effective clinical management, yet it remains a challenging task prone to subjectivity and inter-observer variability. In this study, we propose a novel approach utilizing deep learning classifiers to automate the grading process of knee OA based on the Kellgren Lawrence grading system. Through the development and evaluation of multiple deep learning models, we aim to provide a robust and reliable tool for clinicians to objectively assess OA severity from X-ray images. Our methodology involves preprocessing of X-ray images, followed by feature extraction and classification using convolutional neural networks (CNNs). The performance of each model is assessed through rigorous validation on a diverse dataset of knee X-ray images annotated with ground truth Kellgren Lawrence grades. 2024-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6975/1/fyp_CS_2024_NJ.pdf Ng, Jevyline (2024) Knee osteoarthritis grading using deep learning classifier. Final Year Project, UTAR. http://eprints.utar.edu.my/6975/ |
| spellingShingle | R Medicine (General) RB Pathology T Technology (General) TD Environmental technology. Sanitary engineering Ng, Jevyline Knee osteoarthritis grading using deep learning classifier |
| title | Knee osteoarthritis grading using deep learning classifier |
| title_full | Knee osteoarthritis grading using deep learning classifier |
| title_fullStr | Knee osteoarthritis grading using deep learning classifier |
| title_full_unstemmed | Knee osteoarthritis grading using deep learning classifier |
| title_short | Knee osteoarthritis grading using deep learning classifier |
| title_sort | knee osteoarthritis grading using deep learning classifier |
| topic | R Medicine (General) RB Pathology T Technology (General) TD Environmental technology. Sanitary engineering |
| url | http://eprints.utar.edu.my/6975/ http://eprints.utar.edu.my/6975/1/fyp_CS_2024_NJ.pdf |