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Light-Tissue Interaction Model for the Analysis of Skin Ulcer Multi-spectral Images

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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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01861360
Contributor : Le2i - Université de Bourgogne <>
Submitted on : Tuesday, July 6, 2021 - 5:42:41 PM
Last modification on : Wednesday, July 7, 2021 - 2:29:17 PM

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July Galeano, Pedro José Tapia-Escalante,, Sandra Milena Perez-Buitrago,, Yesid Hernandez-Hoyo, Luisa Fernanda Arias-Munoz, et al.. Light-Tissue Interaction Model for the Analysis of Skin Ulcer Multi-spectral Images. 6th ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE), ECCOMAS, Oct 2017, Porto, Portugal. pp.754-761, ⟨10.1007/978-3-319-68195-5_81⟩. ⟨hal-01861360⟩

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