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The use of facial modeling and analysis to objectively quantify facial redness
Author(s) -
Foolad Negar,
Prakash Neha,
Shi Vivian Y,
Kamangar Faranak,
Wang Qinlu,
Li ChinShang,
Sivamani Raja K
Publication year - 2016
Publication title -
journal of cosmetic dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.626
H-Index - 44
eISSN - 1473-2165
pISSN - 1473-2130
DOI - 10.1111/jocd.12191
Subject(s) - grading (engineering) , erythema , artificial intelligence , medicine , computer science , dermatology , civil engineering , engineering
Summary Background The reproducible evaluation of facial redness is critical to the assessment of erythematotelangiectatic rosacea. Assessments have typically focused on the use of photography with the use of semi‐quantitative grading scales based on evaluator rating. However, few studies have utilized computer‐based algorithms to evaluate facial redness. Aim The purpose of this clinical study was to assess whether there is correlation between clinical grading of facial redness to the assessment of a quantitative computer‐based facial modeling and measurement. Material and Methods In this prospective study, a set of high‐resolution facial photographs and cross‐polarized subsurface photographs for erythema detection were obtained for 31 study participants. A computer algorithm was then utilized to detect and quantify facial redness in the photographs and compare this to semi‐quantitative evaluator‐based grading for facial redness. Results There was a strong correlation between computer‐based cross‐polarized subsurface erythema quantification and clinical grading for redness intensity (Clinical Erythema Assessment), redness distribution, and overall redness severity (Modified Clinical Erythema Assessment). Conclusion Overall, facial redness measurements by facial imaging and computer analysis correlated well to clinical grading scales for both redness intensity and distribution. Future studies should incorporate facial modeling and analysis tools for assessments in clinical studies to introduce greater objectivity and quantitative analysis in facial erythema‐based analyses.