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Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting

The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in...

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Autores principales: Pineda, Jesus, Vargas, Raul, Romero, Lenny A., Marrugo, Javier, Meneses, Jaime, Marrugo, Andres G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802838/
https://www.ncbi.nlm.nih.gov/pubmed/31634361
http://dx.doi.org/10.1371/journal.pone.0223623
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author Pineda, Jesus
Vargas, Raul
Romero, Lenny A.
Marrugo, Javier
Meneses, Jaime
Marrugo, Andres G.
author_facet Pineda, Jesus
Vargas, Raul
Romero, Lenny A.
Marrugo, Javier
Meneses, Jaime
Marrugo, Andres G.
author_sort Pineda, Jesus
collection PubMed
description The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT.
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spelling pubmed-68028382019-11-02 Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting Pineda, Jesus Vargas, Raul Romero, Lenny A. Marrugo, Javier Meneses, Jaime Marrugo, Andres G. PLoS One Research Article The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT. Public Library of Science 2019-10-21 /pmc/articles/PMC6802838/ /pubmed/31634361 http://dx.doi.org/10.1371/journal.pone.0223623 Text en © 2019 Pineda et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Pineda, Jesus
Vargas, Raul
Romero, Lenny A.
Marrugo, Javier
Meneses, Jaime
Marrugo, Andres G.
Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title_full Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title_fullStr Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title_full_unstemmed Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title_short Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting
title_sort robust automated reading of the skin prick test via 3d imaging and parametric surface fitting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802838/
https://www.ncbi.nlm.nih.gov/pubmed/31634361
http://dx.doi.org/10.1371/journal.pone.0223623
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