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Proceedings Paper

Colour and multispectral imaging for wound healing evaluation in the context of a comparative preclinical study
Author(s): Dorra Nouri; Yves Lucas; Sylvie Treuillet; R. Jolivot; F. Marzani
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Paper Abstract

Accurate wound assessment is a critical task for patient care and health cost reduction at hospital but even still worse in the context of clinical studies in laboratory. This task, completely devoted to nurses, still relies on manual and tedious practices. Wound shape is measured with rules, tracing papers or rarely with alginate castings and serum injection. The wound tissues proportion is also estimated by a qualitative visual assessment based on the red-yellow-black code. Further to our preceding works on wound 3D complete assessment using a simple freehanded digital camera, we explore here the adaptation of this tool to wounds artificially created for experimentation purposes. It results that tissue uniformity and flatness leads to a simplified approach but requires multispectral imaging for enhanced wound delineation. We demonstrate that, in this context, a simple active contour method can successfully replace more complex tools such as SVM supervised classification, as no training step is required and that one shot is enough to deal with perspective projection errors. Moreover, involving all the spectral response of the tissue and not only RGB components provides a higher discrimination for separating healed epithelial tissue from granulation tissue. This research work is part of a comparative preclinical study on healing wounds. It aims to compare the efficiency of specific medical honeys with classical pharmaceuticals for wound care. Results revealed that medical honey competes with more expensive pharmaceuticals.

Paper Details

Date Published: 13 March 2013
PDF: 10 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866923 (13 March 2013); doi: 10.1117/12.2003943
Show Author Affiliations
Dorra Nouri, Lab. PRISME, Univ. d'Orléans (France)
Yves Lucas, Lab. PRISME, Univ. d'Orléans (France)
Sylvie Treuillet, Lab. PRISME, Univ. d'Orléans (France)
R. Jolivot, LE2i UFR Sciences et Techniques, Univ. de Bourgogne (France)
F. Marzani, LE2i UFR Sciences et Techniques, Univ. de Bourgogne (France)

Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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