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This article is cited in 12 scientific papers (total in 12 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
Hyperspectral in vivo analysis of normal skin chromophores and visualization of oncological pathologies
V. Sherendaka, I. A. Bratchenkoa, O. O. Myakinina, P. Volkhina, Yu. Khristoforovaa, A. A. Moryatovb, A. S. Machikhinc, V. È. Pozharc, S. V. Kozlovb, V. P. Zakharova a Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia; 2 Samara State Medical University, Samara, Russia
b Samara State Medical University, Samara, Russia
c Scientific and Technological Center of Unique Instrumentation RAS, Moscow, Russia
Abstract:
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.
Keywords:
hyperspectral imaging, chromophores, melanin, hemoglobin, oncopathology, malignant melanoma, basal cell carcinoma, acousto-optical video spectrometer, optical density, chromophore index, classification.
Received: 03.05.2018 Accepted: 24.05.2019
Citation:
V. Sherendak, I. A. Bratchenko, O. O. Myakinin, P. Volkhin, Yu. Khristoforova, A. A. Moryatov, A. S. Machikhin, V. È. Pozhar, S. V. Kozlov, V. P. Zakharov, “Hyperspectral in vivo analysis of normal skin chromophores and visualization of oncological pathologies”, Computer Optics, 43:4 (2019), 661–670
Linking options:
https://www.mathnet.ru/eng/co690 https://www.mathnet.ru/eng/co/v43/i4/p661
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Abstract page: | 197 | Full-text PDF : | 80 | References: | 31 |
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