Smart Knee X-Ray Analysis for Osteoarthritis Diagnosis

Smart Knee X-Ray Analysis for Osteoarthritis: An Overview Diagnosis is a machine learning method designed to improve osteoarthritis identification. Millions of people worldwide suffer from osteoarthritis, a degenerative joint condition that causes pain, stiffness, and decreased mobility. In this study, preprocessing methods including data purification and feature extraction are used to evaluate knee X-ray pictures. Machine learning techniques CNN, SVM, and Random Forest are utilized to categorize patients as either normal or having osteoarthritis. By automating diagnostics, the technique improves accuracy and enables early detection. Deep learning is incorporated to guarantee consistent results and give medical professionals an intuitive interface. This strategy aims to enhance patient outcomes, encourage prompt intervention, and lessen long-term joint degeneration. Key words: computer vision, image processing, guidance system, and object recognition.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-14
DOI
https://doi.org/10.55041/ijsrem47779
Primary Topic
Medical Imaging and Analysis
Type
article
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article

Smart Knee X-Ray Analysis for Osteoarthritis Diagnosis

Carounanidy Usha
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Medical Imaging and Analysis
article

Smart Knee X-Ray Analysis for Osteoarthritis Diagnosis

Carounanidy Usha
article en

Abstract

Smart Knee X-Ray Analysis for Osteoarthritis: An Overview Diagnosis is a machine learning method designed to improve osteoarthritis identification. Millions of people worldwide suffer from osteoarthritis, a degenerative joint condition that causes pain, stiffness, and decreased mobility. In this study, preprocessing methods including data purification and feature extraction are used to evaluate knee X-ray pictures. Machine learning techniques CNN, SVM, and Random Forest are utilized to categorize patients as either normal or having osteoarthritis. By automating diagnostics, the technique improves accuracy and enables early detection. Deep learning is incorporated to guarantee consistent results and give medical professionals an intuitive interface. This strategy aims to enhance patient outcomes, encourage prompt intervention, and lessen long-term joint degeneration. Key words: computer vision, image processing, guidance system, and object recognition.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 90%
Medical Imaging and Analysis
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