Analysis of Cutaneous Leishmaniasis Hyperspectral Images by Means of an Inverse Modeling Procedure

Latin America and other places in the world have tropical regions, from which multiple diseases emerge. Cutaneous Leishmaniasis (CL) is one of the most common pathologies that attack the populations on these areas, generating an ulcer and leaving marks for life. The difficult access to appropriate medical attention of affected populations raises the need for new instruments and techniques that facilitate the diagnosis and monitoring of treatments for this disease. This article proposes a methodology of analysis of golden hamster skin with cutaneous ulcer caused by leishmaniasis through a three-layer inverse reflectance model, genetic algorithms and the Hyperspectral image acquisition system ASCLEPIOS. As a result, the concentration maps of: thickness of the epidermis (epi), epidermis plus thickness of the dermis (epiPder), volumetric fraction of blood (Fblood), diameter of the Collagen particles (Coll), volumetric fraction of collagen (Fcoll), diameter of the Fibroblast particles (Fibro), volumetric fraction of melanin (Fmel), diameter of Keratynocytes particles (Kera), diameter of Macrophages particles (Macro), and oxygen saturation (OS) were obtained. The ANOVA test on the concentration maps was used. In this way, it is observed which variables allow to statistically differentiate healthy tissue from nodular tissue and ulcer center, in this way it is observed that fibroblasts and oxygen saturation are the parameters that statistically differentiate healthy tissue to tissue with nodule. In the case of healthy tissue and ulcer center, the differentiating parameters are fibroblasts and volumetric fraction of melanin.