Colour and multispectral imaging for wound healing evaluation in the context of a comparative preclinical study
| Autor: | Franck Marzani, Yves Lucas, Romuald Jolivot, Dorra Nouri, Sylvie Treuillet |
|---|---|
| Přispěvatelé: | Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique ( PRISME ), Université d'Orléans ( UO ) -Ecole Nationale Supérieure d'Ingénieurs de Bourges ( ENSI Bourges ), Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique (PRISME), Ecole Nationale Supérieure d'Ingénieurs de Bourges (ENSI Bourges)-Université d'Orléans (UO), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing
active contour Computer science Multispectral image KNN classification wound assessment 02 engineering and technology [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing Machine learning computer.software_genre 030218 nuclear medicine & medical imaging 03 medical and health sciences Wound assessment Wound care 0302 clinical medicine [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing 0202 electrical engineering electronic engineering information engineering medicine multispectral imaging Healing wounds Active contour model business.industry Granulation tissue Image segmentation SVM classification 3. Good health medicine.anatomical_structure 020201 artificial intelligence & image processing Artificial intelligence business Wound healing computer [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | Proc. SPIE 8669, Medical Imaging 2013: Image Processing Medical Imaging 2013: Image Processing Medical Imaging 2013: Image Processing, Feb 2013, ake Buena Vista (Orlando Area), Florida, United States. pp.866923, 2013, 〈10.1117/12.2003943〉 Medical Imaging 2013: Image Processing, Feb 2013, ake Buena Vista (Orlando Area), Florida, United States. pp.866923, ⟨10.1117/12.2003943⟩ Medical Imaging: Image Processing |
| DOI: | 10.1117/12.2003943〉 |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|