Paper
9 April 2020 Neural-network-based classification of skin structural elements in case of urticaria using histological RGB images
Author Affiliations +
Proceedings Volume 11457, Saratov Fall Meeting 2019: Optical and Nano-Technologies for Biology and Medicine; 114571Z (2020) https://doi.org/10.1117/12.2560510
Event: Saratov Fall Meeting 2019: VII International Symposium on Optics and Biophotonics, 2019, Saratov, Russian Federation
Abstract
We address the problem of differential diagnostics of chronic spontaneous urticaria and urticarial vasculitis. The clinical pictures of these two allergy diagnoses are similar, however a well-trained pathologist can see the differences in skin tissue on the microscopic level, and thus the histological study of skin biopsy is usually performed to prescribe the right treatment. To increase the throughput and quality of the histological study and differential diagnostics of chronic spontaneous urticaria and urticarial vasculitis, we propose an imaging system with neural-network-based classification of skin tissue structures. The capabilities of a hyperspectral microscopic visualization system with acousto-optical module for increasing the efficiency of neural network training are also being considered.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. V. Shirokov, A. M. Borbat, O. V. Polschikova, E. D. Lovchikova, I. V. Danilycheva, M. V. Danilychev, and O. R. Katunina "Neural-network-based classification of skin structural elements in case of urticaria using histological RGB images", Proc. SPIE 11457, Saratov Fall Meeting 2019: Optical and Nano-Technologies for Biology and Medicine, 114571Z (9 April 2020); https://doi.org/10.1117/12.2560510
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KEYWORDS
Skin

Neural networks

RGB color model

Diagnostics

Tissues

Ultraviolet radiation

Image processing

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