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Hyperspectral Imaging and Classification for Grading Skin Erythema

Abstract : Erythema is an inflammatory condition of the skin that is commonly used as a feature to monitor the progression of cutaneous diseases or treatment induced side effects. In radiation therapy, skin erythema is routinely assessed visually by an expert using standardized grading criteria. However, visual assessment (VA) is subjective and commonly used grading tools are too coarse to score the onset of erythema. Therefore, an objective method capable of quantitatively grading early erythema changes may help identify patients at higher risk for developing severe radiation induced skin toxicities. The purpose of this study is to investigate the feasibility of using hyperspectral imaging (HSI) for quantitative assessment of early erythema and to characterize its performance against VA documented on conventional digital photographic red-green-blue (RGB) images. Erythema was induced artificially on 3 volunteers in a controlled pilot study; and was subsequently measured using HSI and color imaging. HSI and color imaging data was analyzed using linear discriminant analysis (LDA) to perform classification. The classification results, including accuracy, and precision, demonstrated that HSI is superior to color imaging in skin erythema assessment.
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https://hal.inria.fr/hal-01869944
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Submitted on : Friday, September 7, 2018 - 3:57:25 AM
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Long-term archiving on: : Saturday, December 8, 2018 - 12:42:44 PM

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Ramy Abdlaty, Lilian Doerwald-Munoz, Ali Madooei, Samir Sahli, Shu-Chi A Yeh, et al.. Hyperspectral Imaging and Classification for Grading Skin Erythema. Frontiers in Physics, Frontiers, 2018, 6, pp.1-10. ⟨10.3389/fphy.2018.00072⟩. ⟨hal-01869944⟩

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