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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM31183
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Medical imaging plays a pivotal role in the early detection and accurate classification of musculoskeletal disorders. This study focuses on the development of a robust and efficient system for the detection and classification of two prevalent musculoskeletal conditions: scoliosis and knee osteoarthritis, using X-ray images. Scoliosis is a lateral curvature of the spine, while knee osteoarthritis involves the degeneration of knee joint cartilage and underlying bone.The proposed system leverages state-of-the-art deep learning techniques to automatically detect and classify these conditions from X-ray images. The workflow involves three main stages: preprocessing, feature extraction, and classification. During preprocessing, the X-ray images are normalized, noise-reduced, and anatomical landmarks are identified for accurate alignment.
KEYWORDS
Publication Date
12/31/45401
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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