In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum

Ivan A. Bratchenko (Login required)
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation

Violetta P. Sherendak
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation

Oleg O. Myakinin
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation

Dmitry N. Artemyev
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation

Alexander A. Moryatov
Department of Oncology, Samara State Medical University, Russian Federation
Samara Regional Clinical Oncology Dispensary, Russian Federation

Ekaterina Borisova
Institute of Electronics, Bulgarian Academy of Sciences, Sofia, Bulgaria

Latchezar Avramov
Institute of Electronics, Bulgarian Academy of Sciences, Sofia, Bulgaria

Larisa A. Zherdeva
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation

Andrey E. Orlov
Samara Regional Clinical Oncology Dispensary, Russian Federation

Sergey V. Kozlov
Department of Oncology, Samara State Medical University, Russian Federation
Samara Regional Clinical Oncology Dispensary, Russian Federation

Valery P. Zakharov
Department of Laser and Biotechnical Systems, Samara National Research University, Russian Federation


Paper #3252 received 10 Sep 2017; revised manuscript received 2 Oct 2017; accepted for publication 4 Oct 2017; published online 16 Jan 2018.

DOI: 10.18287/JBPE17.04.010301

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. 

Keywords

hyperspectral imaging; backscattering spectroscopy; oncodermatology; oncological diagnostics; melanoma; nevi; carcinoma; melanin; hemoglobin content

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