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Construction of a knee osteoarthritis diagnostic system based on X-ray image processing

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Abstract

In order to accurately diagnose knee osteoarthritis, a detection technique as well as its quantitative assessment based on X-ray image processing is proposed in this study. First, image segmentation is implemented on the basis of maximum between-class variance and region growing method. Second, the edge of the image concerned is filled based on calculations of mathematical morphology, followed by edge extraction, which realizes extraction of the image in the region of interest. Finally, processing and judgment concerning four indicators to determine knee osteoarthritis, namely, joint space asymmetry, articular sclerosis, rugged articular surface, and intra-articular loose bodies, were judged and judged. Our experimental results show that this technique can effectively detect and describe the features of knee osteoarthritis, which can be used as a tool for clinical diagnosis.

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Acknowledgements

The project is funded by Zhejiang Science and Technology Department Public Welfare Project (Grant: 2017C35001) and Ningbo Municipal Bureau of Science and Technology Project (Grants: 2017A10027, 2017C50023, 2016C10056).

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Authors and Affiliations

  1. School of Information and Engineering, Ningbo Dahongying University, Ningbo, China

    Yongping Li

  2. Tianlin Community Health Center, Xuhui District, Shanghai, China

    Ning Xu

  3. School of Engineering, University of Guelph, Guelph, Canada

    Qiang Lyu

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  1. Yongping Li
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  2. Ning Xu
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Correspondence to Yongping Li.

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Li, Y., Xu, N. & Lyu, Q. Construction of a knee osteoarthritis diagnostic system based on X-ray image processing. Cluster Comput 22 (Suppl 6), 15533–15540 (2019). https://doi.org/10.1007/s10586-018-2677-y

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