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Scar tissue classification using nonlinear optical microscopy and discriminant analysis

Timothy Andrew Kelf, Martin Gosnell, Bjornar Sandnes Orcid Logo, Anna E Guller, Anatoly B Shekhter, Andrei V Zvyagin

Journal of Biophotonics, Volume: 5, Issue: 2, Pages: 159 - 167

Swansea University Author: Bjornar Sandnes Orcid Logo

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DOI (Published version): 10.1002/jbio.201100075

Published in: Journal of Biophotonics
ISSN: 1864-063X
Published: 2012
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Item Description: The paper demonstrated a novel automated procedure for classification of human scars according to maturation stage, achieving accuracy as high as 96%. Non-linear optical microscopy was used to isolate the characteristic collagen morphologies, and image analysis combined with discriminant analysis and genetic algorithms were used to identify and classify the scar types. The methodology holds promise for express scar diagnosis, deemed especially useful in the paediatric practices. The paper further demonstrates the first use of unbiased computer based methods to probe the heterogeneous composite scar tissue organization.
College: Faculty of Science and Engineering
Issue: 2
Start Page: 159
End Page: 167