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Robust tissue classification for reproducible wound assessment in telemedicine environments

[+] Author Affiliations
Hazem Wannous

Université d’Orléans, Institut PRISME – Polytechnique Orléans, 45067 Orléans cedex 2, France

Sylvie Treuillet

Université d’Orléans, Institut PRISME – Polytechnique Orléans, 45067 Orléans cedex 2, France

Yves Lucas

Université d’Orléans, Institut PRISME – Polytechnique Bourges, 63 avenue de Lattre, 18020 Bourges cedex, France

J. Electron. Imaging. 19(2), 023002 (April 08, 2010). doi:10.1117/1.3378149
History: Received May 07, 2009; Revised February 16, 2010; Accepted February 22, 2010; Published April 08, 2010; Online April 08, 2010
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In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

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© 2010 SPIE and IS&T

Citation

Hazem Wannous ; Sylvie Treuillet and Yves Lucas
"Robust tissue classification for reproducible wound assessment in telemedicine environments", J. Electron. Imaging. 19(2), 023002 (April 08, 2010). ; http://dx.doi.org/10.1117/1.3378149


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