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A Novel Method to Determine Patient Skin Type: The Skin Analyzer
Measuring skin color for medical research in an objective and nonbiased manner usually requires expensive equipment such as spectrophotometry and requires the subject to be present in person. We present a novel method to measure skin color from photographs using the Skin Analyzer application as a mo...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566767/ https://www.ncbi.nlm.nih.gov/pubmed/37829105 http://dx.doi.org/10.1097/GOX.0000000000005341 |
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author | Mohamed, Youssef Koussayer, Bilal Randolph, Ellie M. West, William Morris, Julia A. Le, Nicole K. Whalen, Kristen Gemayel, Kristina Al Bayati, Mahmood J. Troy, Jared Laun, Jake |
author_facet | Mohamed, Youssef Koussayer, Bilal Randolph, Ellie M. West, William Morris, Julia A. Le, Nicole K. Whalen, Kristen Gemayel, Kristina Al Bayati, Mahmood J. Troy, Jared Laun, Jake |
author_sort | Mohamed, Youssef |
collection | PubMed |
description | Measuring skin color for medical research in an objective and nonbiased manner usually requires expensive equipment such as spectrophotometry and requires the subject to be present in person. We present a novel method to measure skin color from photographs using the Skin Analyzer application as a more effective, accessible, and efficient alternative. A desktop application, the Skin Analyzer, was developed to convert skin samples collected from digital images to the L*a*b color space and uses those values to calculate an individual typology angle that correlates to a Fitzpatrick skin type. To assess accuracy in variable lighting, six known colors representing the six Fitzpatrick skin types were printed and photographed in 15 separate locations within the hospital. To account for user variability in sample selection, interrater reliability was calculated with data generated by 13 untrained users testing the app on six subjects. The accuracy of measuring known values, which is the classification accuracy, was calculated to be 80%. Krippendorff alpha test was used to evaluate interrater reliability. The obtained alpha of 0.84 indicates a high interrater reliability. The high accuracy and reliability make the Skin Analyzer a suitable method of objectively determining Fitzpatrick skin type from images. The app may be used to investigate the effects of skin tone in various areas of interest, especially in retrospective studies where skin colorimeters cannot be used. |
format | Online Article Text |
id | pubmed-10566767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-105667672023-10-12 A Novel Method to Determine Patient Skin Type: The Skin Analyzer Mohamed, Youssef Koussayer, Bilal Randolph, Ellie M. West, William Morris, Julia A. Le, Nicole K. Whalen, Kristen Gemayel, Kristina Al Bayati, Mahmood J. Troy, Jared Laun, Jake Plast Reconstr Surg Glob Open Technology Measuring skin color for medical research in an objective and nonbiased manner usually requires expensive equipment such as spectrophotometry and requires the subject to be present in person. We present a novel method to measure skin color from photographs using the Skin Analyzer application as a more effective, accessible, and efficient alternative. A desktop application, the Skin Analyzer, was developed to convert skin samples collected from digital images to the L*a*b color space and uses those values to calculate an individual typology angle that correlates to a Fitzpatrick skin type. To assess accuracy in variable lighting, six known colors representing the six Fitzpatrick skin types were printed and photographed in 15 separate locations within the hospital. To account for user variability in sample selection, interrater reliability was calculated with data generated by 13 untrained users testing the app on six subjects. The accuracy of measuring known values, which is the classification accuracy, was calculated to be 80%. Krippendorff alpha test was used to evaluate interrater reliability. The obtained alpha of 0.84 indicates a high interrater reliability. The high accuracy and reliability make the Skin Analyzer a suitable method of objectively determining Fitzpatrick skin type from images. The app may be used to investigate the effects of skin tone in various areas of interest, especially in retrospective studies where skin colorimeters cannot be used. Lippincott Williams & Wilkins 2023-10-11 /pmc/articles/PMC10566767/ /pubmed/37829105 http://dx.doi.org/10.1097/GOX.0000000000005341 Text en Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Technology Mohamed, Youssef Koussayer, Bilal Randolph, Ellie M. West, William Morris, Julia A. Le, Nicole K. Whalen, Kristen Gemayel, Kristina Al Bayati, Mahmood J. Troy, Jared Laun, Jake A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title | A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title_full | A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title_fullStr | A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title_full_unstemmed | A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title_short | A Novel Method to Determine Patient Skin Type: The Skin Analyzer |
title_sort | novel method to determine patient skin type: the skin analyzer |
topic | Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566767/ https://www.ncbi.nlm.nih.gov/pubmed/37829105 http://dx.doi.org/10.1097/GOX.0000000000005341 |
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