Abstract. The paper presents analysis of hyperspectral images for human skin cancer pathologies diagnostics. Hyperspectral images data contained backscattered spectra of normal skin and tumors. Analysis of hyperspectral images provided information about hemoglobin and melanin content for the differentiation of malignant and benign skin neoplasms based on tissues optical density calculation. It was shown that the accuracy of cancerous tissues classification reaches 88% for proposed algorithm of hyperspectral images analysis. The proposed approach may be a rapid and reliable tool for skin oncological diseases screening. © 2018 Journal of Biomedical Photonics & Engineering.Keywords: hyperspectral imaging; backscattering spectroscopy; oncodermatology; oncological diagnostics; melanoma; nevi; carcinoma; melanin; hemoglobin content.

In the paper, we present test results of methods for the noninvasive diagnosis of skin neoplasms, based on the hyperspectral registration of images by using a camera with an acousto-optic tunable filter. For the identification of oncological pathologies, an integral spectral index has been proposed for a set of concentric regions around the source of neoplasm growth for the tissue sample under study. As well as taking account of changes in the spectral properties of the tissue, the introduced index indirectly takes into account classical ABCD dermatoscopic features: asymmetry, border irregularity, color diversity, and the tumor diameter. Results of training set separating are presented and the applicability of the proposed approaches to the clinical practice is shown.

We present results of main skin chromophores (melanin and hemoglobin) optical analysis. Analysis of 91 in vivo skin tissues (50 benign and 41 malignant) was performed in visible spectral region with hyperspectral imaging technique. To assess the malignancy of skin tissues we proposed two methods for calculating the integral index of tissue optical density and performed a comparison of their effectiveness and effectiveness of physician survey. As the main diagnostic feature, we propose to use data of integral optical index dispersion from the studied tissue and healthy tissue area. The results of skin tissues classification with discriminant analysis are presented. The possibility of the proposed approaches application in the clinical practice is shown.