Knee Osteoarthritis Detection and It’s Severity CNN
DOI:
https://doi.org/10.32628/CSEIT2410322Keywords:
Convolutional Neural Networks, Osteoarthritis, X-raysAbstract
Osteoarthritis (OA) of the knee is a common degenerative joint disease that is characterized by inflammation and cartilage degradation, which results in pain and impairment. For prompt intervention and care, early detection and precise assessment of the severity of OA are essential. In this research, we offer a unique method for automated knee OA diagnosis and severity assessment using medical imaging data, especially X-ray images, using convolutional neural networks (CNNs). Our CNN architecture is intended to identify complex features from knee X-rays and categorize them into various OA severity levels, from moderate to severe. A sizable dataset of knee X-ray pictures with accompanying OA severity scores is used by the suggested model. Our method shows promise in correctly detecting knee OA after thorough testing and validation on a variety of datasets.
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