A constituent-based preprocessing approach for characterising cartilage using NIR absorbance measurements
Journal article
Authors | Brown, Cameron P. and Chen, Minsi |
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Abstract | Near-infrared spectroscopy is a widely adopted technique for characterising biological tissues. The high dimensionality of spectral data, however, presents a major challenge for analysis. Here, we present a second-derivative Beer's law-based technique aimed at projecting spectral data onto a lower dimension feature space characterised by the constituents of the target tissue type. This is intended as a preprocessing step to provide a physically-based, low dimensionality input to predictive models. Testing the proposed technique on an experimental set of 145 bovine cartilage samples before and after enzymatic degradation, produced a clear visual separation between the normal and degraded groups. Reduced proteoglycan and collagen concentrations, and increased water concentrations were predicted by simple linear fitting following degradation (all $p\ll 0.05$). Classification accuracy using the Mahalanobis distance was $\gt 98\%$ between these groups. |
Keywords | Cartilage; Osteoarthritis; Near-infrared spectroscopy |
Year | 2016 |
Journal | Biomedical Physics & Engineering Express |
Publisher | IOP Publishing Ltd |
ISSN | 2057-1976 |
Digital Object Identifier (DOI) | https://doi.org/10.1088/2057-1976/2/1/017002 |
Web address (URL) | http://hdl.handle.net/10545/620880 |
hdl:10545/620880 | |
Publication dates | 18 Jan 2016 |
Publication process dates | |
Deposited | 16 Nov 2016, 18:37 |
Rights | Archived with thanks to Biomedical Physics & Engineering Express |
Contributors | University of Oxford and University of Derby |
File | File Access Level Open |
File | File Access Level Open |
https://repository.derby.ac.uk/item/92wq8/a-constituent-based-preprocessing-approach-for-characterising-cartilage-using-nir-absorbance-measurements
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