Abstract
Skin ulcers (SU) are ones of the most frequent causes of consultation in primary health-care units (PHU) in tropical areas. However, the lack of specialized physicians in those areas, leads to improper diagnosis and management of the patients. There is then a need to develop tools that allow guiding the physicians toward a more accurate diagnosis. Multi-spectral imaging systems are a potential non-invasive tool that could be used in the analysis of skin ulcers. With these systems it is possible to acquire optical images at different wavelengths which can then be processed by means of mathematical models based on optimization approaches. The processing of those kind of images leads to the quantification of the main components of the skin. In the case of skin ulcers, these components could be correlated to the different stages of wound healing during the follow-up of a skin ulcer. This article presents the processing of a skin ulcer multi-spectral image. The ulcer corresponds to Leishmaniasis which is one of the diseases the most prominent in tropical areas. The image processing is performed by means of a light-tissue interaction model based on the distribution of the skin as a semi-infinite layer. The model, together with an optimization approach allows quantifying the main light-absorbing and scattering skin-parameters in the visible and near-infrared range. The results show significant differences between healthy and unhealthy area of the image.
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References
Galeano, J., Jolivot, R., Marzani, F., Benezeth, Y.: Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm. Biomed. Sig. Process. Control 82, 169–175 (2013)
Jolivot, R., Benezeth, Y., Marzani, F.: Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology. Int. J. Biomed. Imaging 26, 1–16 (2013)
Galeano, J., Jolivot, R., Benezeth, Y., Marzani, F., Emile, J.-F., Lamarque, D.: Analysis of multispectral images of excised colon tissue samples based on genetic algorithms. In: 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (SITIS), pp. 833–838. IEEE (2012)
Galeano, J., Perez, S., Montoya, Y., Botina, D., Garzón, J.: Blind source separation of ex-vivo aorta tissue multispectral images. Biomed. Opt. Express 65, 1589–1598 (2015)
Jacques, S.L.: Optical properties of biological tissues: a review. Phys. Med. Biol. 5811, R37 (2013)
Tuchin, V.V.: Tissue optics: light scattering methods and instruments for medical diagnosis. In: SPIE-International Society for Optical Engineering (2007)
Jolivot, R., Vabres, P., Marzani, F.: Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system. Comput. Med. Imaging Graph. 352, 8588 (2011)
Mansouri, A., Marzani, F., Gouton, P.: Neural networks in two cascade algorithms for spectral reflectance reconstruction. In: ICIP, p. 718721 (2005)
Zonios, G., Aikaterini, D.: Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties. Opt. Express 1419, 8661–8674 (2006)
Mätzler, C.: MATLAB functions for Mie scattering and absorption, version 2. IAP Res. Rep. 8, 1–24 (2002)
Yudovsky, D., Laurent, P.: Rapid and accurate estimation of blood saturation, melanin content, and epidermis thickness from spectral diffuse reflectance. Appl. Opt. 4910, 1707–1719 (2010)
Rao, S.S., Rao, S.S.: Engineering Optimization: Theory and Practice. Wiley, Hoboken (2009)
UdDin, S., Greaves, N.S., Anil, S., Baguneid, M., Bayat, B.: Noninvasive device readouts validated by immunohistochemical analysis enable objective quantitative assessment of acute wound healing in human skin. Wound Repair Regen. 236, 901–914 (2015)
Acknowledgements
The authors would like to acknowledge the medical support given by Dr. Brunella Raymundo Villalva and Dr. Francisco Bravo Puccio from Hospital Cayetano Heredia Lima-Perú. Also we acknowledge the support given by Dr. Benjamín Catañeda from Pontificia Universidad Católica del Perú and Dr. Jorge Arevalo from Universidad Peruana Cayetano Heredia. The authors also acknowledge the financial support given by the SticAmSud program (COLCIENCIA-INRIA-CONCYTEC) for the creation of the academical network IMPULSO (IMage Processing of skin ULcerS in trOpical areas).
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Galeano, J. et al. (2018). Light-Tissue Interaction Model for the Analysis of Skin Ulcer Multi-spectral Images. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_81
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DOI: https://doi.org/10.1007/978-3-319-68195-5_81
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