Tissue optical properties combined with machine learning enables estimation of articular cartilage composition and functional integrity

组织光学特性与机器学习相结合,可以用于评估关节软骨的成分和功能完整性。

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Abstract

Absorption and reduced scattering coefficients ( μa, μs' ) of biological tissues have shown significant potential in biomedical applications. Thus, they are effective parameters for the characterization of tissue integrity and provide vital information on the health of biological tissues. This study investigates the potential of optical properties ( μa, μs' ) for estimating articular cartilage composition and biomechanical properties using multivariate and machine learning techniques. The results suggest that μ(a) could optimally estimate cartilage proteoglycan content in the superficial zone, in addition to its equilibrium modulus. While μs' could effectively estimate the proteoglycan content of the middle and deep zones in addition to the instantaneous and dynamic moduli of articular cartilage.

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