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Hyperspectral image processing for detection and grading of skin erythema
Author(s) -
Ali Madooei,
Ramy Abdlaty,
Lilian Doerwald-Munoz,
Joseph E. Hayward,
Mark S. Drew,
Qiyin Fang,
Josiane Zerubia
Publication year - 2017
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2254132
Subject(s) - hyperspectral imaging , computer science , artificial intelligence , erythema , grading (engineering) , image processing , computer vision , pipeline (software) , rgb color model , pattern recognition (psychology) , dermatology , image (mathematics) , medicine , civil engineering , engineering , programming language
Visual assessment is the most common clinical investigation of skin reactions in radiotherapy. Due to the subjective nature of this method, additional noninvasive techniques are needed for more accurate evaluation. Our goal is to evaluate the effectiveness of hyperspectral image analysis for that purpose. In this pilot study, we focused on detection and grading of skin Erythema. This paper reports our proposed processing pipeline and experimental findings. Experiments have been performed to demonstrate the efficacy of the proposed approach for (1) reproducing clinical assessments, and (2) outperforming RGB imaging data.

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