A constituent-based preprocessing approach for characterising cartilage using NIR absorbance measurements

Journal article

Brown, Cameron P. and Chen, Minsi 2016. A constituent-based preprocessing approach for characterising cartilage using NIR absorbance measurements. Biomedical Physics & Engineering Express. https://doi.org/10.1088/2057-1976/2/1/017002
AuthorsBrown, Cameron P. and Chen, Minsi

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.

KeywordsCartilage; Osteoarthritis; Near-infrared spectroscopy
JournalBiomedical Physics & Engineering Express
PublisherIOP Publishing Ltd
Digital Object Identifier (DOI)https://doi.org/10.1088/2057-1976/2/1/017002
Web address (URL)http://hdl.handle.net/10545/620880
Publication dates18 Jan 2016
Publication process dates
Deposited16 Nov 2016, 18:37

Archived with thanks to Biomedical Physics & Engineering Express

ContributorsUniversity of Oxford and University of Derby
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