Callus Thickness Determination Adjuvant to Tissue Oximetry Imaging

Gennadi Saiko, Gennadi Saiko

2022

Abstract

Introduction: Corns and calluses are thickened skin due to repeated friction, pressure, or other irritation. While in many cases, calluses are harmless, if not removed timely, they may lead to skin ulceration or infection. Thus, the removal of calluses is an essential part of surgical debridement. Often, healthcare professionals experience problems with their identification. This study aims to develop an approach for callus thickness determination using hyperspectral imaging. Methods: Based on the two-layer tissue model developed by Yudovsky D et al., 2010, we have developed a computationally simple way of extracting the epithelial thickness from spectral measurements of skin reflection. We have performed a numerical evaluation of the proposed algorithm: generated the reflectance spectrum using the two-layer model, added noise, and reconstructed the epidermal thickness L using the proposed method. To evaluate performance, we have used the following parameters: thickness of the epithelium: 0.1-2mm, dermal blood concentration: 0.2%, 3%, and 7%, blood oxygen saturation: 60%, 80%, and 99%. Results: We have found that the model reasonably well extracts epidermal thickness L in the 0.1-1.5mm range. Beyond that, the reflectance signal does not bring information about underlying layers. The most significant factor, which impacts estimation, is the scattering coefficient of the epidermis. Other factors can be mainly ignored. Conclusions: The proposed model can be easily implemented in image processing algorithms for hyperspectral/multispectral imaging systems.

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Paper Citation


in Harvard Style

Saiko G. (2022). Callus Thickness Determination Adjuvant to Tissue Oximetry Imaging. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING, ISBN 978-989-758-552-4, pages 147-152. DOI: 10.5220/0010852400003123


in Bibtex Style

@conference{bioimaging22,
author={Gennadi Saiko},
title={Callus Thickness Determination Adjuvant to Tissue Oximetry Imaging},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING,},
year={2022},
pages={147-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010852400003123},
isbn={978-989-758-552-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING,
TI - Callus Thickness Determination Adjuvant to Tissue Oximetry Imaging
SN - 978-989-758-552-4
AU - Saiko G.
PY - 2022
SP - 147
EP - 152
DO - 10.5220/0010852400003123