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Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis

Medical infrared thermography has proven to be a complementary procedure to physiological disorders, such as the diabetic foot. However, the technique remains essentially based on 2D images that display partial anatomy. In this context, a 3D thermal model provides improved visualization and faster i...

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Autores principales: Mancilla, Rafael Bayareh, Tấn, Bình Phan, Daul, Christian, Martínez, Josefina Gutiérrez, Salas, Lorenzo Leija, Wolf, Didier, Hernández, Arturo Vera
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201207/
https://www.ncbi.nlm.nih.gov/pubmed/34204151
http://dx.doi.org/10.3390/s21113918
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author Mancilla, Rafael Bayareh
Tấn, Bình Phan
Daul, Christian
Martínez, Josefina Gutiérrez
Salas, Lorenzo Leija
Wolf, Didier
Hernández, Arturo Vera
author_facet Mancilla, Rafael Bayareh
Tấn, Bình Phan
Daul, Christian
Martínez, Josefina Gutiérrez
Salas, Lorenzo Leija
Wolf, Didier
Hernández, Arturo Vera
author_sort Mancilla, Rafael Bayareh
collection PubMed
description Medical infrared thermography has proven to be a complementary procedure to physiological disorders, such as the diabetic foot. However, the technique remains essentially based on 2D images that display partial anatomy. In this context, a 3D thermal model provides improved visualization and faster inspection. This paper presents a 3D reconstruction method associated with temperature information. The proposed solution is based on a Structure from Motion and Multi-view Stereo approach, exploiting a set of multimodal merged images. The infrared images were obtained by automatically processing the radiometric data to remove thermal interferences, segment the RoI, enhance false-color contrast, and for multimodal co-registration under a controlled environment and a ∆T < 2.6% between the RoI and thermal interferences. The geometric verification accuracy was 77% ± 2%. Moreover, a normalized error was adjusted per sample based on a linear model to compensate for the curvature emissivity (error ≈ 10% near to 90°). The 3D models were displayed with temperature information and interaction controls to observe any point of view. The temperature sidebar values were assigned with information retrieved only from the RoI. The results have proven the feasibility of the 3D multimodal construction to be used as a promising tool in the diagnosis of diabetic foot.
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spelling pubmed-82012072021-06-15 Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis Mancilla, Rafael Bayareh Tấn, Bình Phan Daul, Christian Martínez, Josefina Gutiérrez Salas, Lorenzo Leija Wolf, Didier Hernández, Arturo Vera Sensors (Basel) Article Medical infrared thermography has proven to be a complementary procedure to physiological disorders, such as the diabetic foot. However, the technique remains essentially based on 2D images that display partial anatomy. In this context, a 3D thermal model provides improved visualization and faster inspection. This paper presents a 3D reconstruction method associated with temperature information. The proposed solution is based on a Structure from Motion and Multi-view Stereo approach, exploiting a set of multimodal merged images. The infrared images were obtained by automatically processing the radiometric data to remove thermal interferences, segment the RoI, enhance false-color contrast, and for multimodal co-registration under a controlled environment and a ∆T < 2.6% between the RoI and thermal interferences. The geometric verification accuracy was 77% ± 2%. Moreover, a normalized error was adjusted per sample based on a linear model to compensate for the curvature emissivity (error ≈ 10% near to 90°). The 3D models were displayed with temperature information and interaction controls to observe any point of view. The temperature sidebar values were assigned with information retrieved only from the RoI. The results have proven the feasibility of the 3D multimodal construction to be used as a promising tool in the diagnosis of diabetic foot. MDPI 2021-06-06 /pmc/articles/PMC8201207/ /pubmed/34204151 http://dx.doi.org/10.3390/s21113918 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mancilla, Rafael Bayareh
Tấn, Bình Phan
Daul, Christian
Martínez, Josefina Gutiérrez
Salas, Lorenzo Leija
Wolf, Didier
Hernández, Arturo Vera
Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title_full Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title_fullStr Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title_full_unstemmed Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title_short Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis
title_sort anatomical 3d modeling using ir sensors and radiometric processing based on structure from motion: towards a tool for the diabetic foot diagnosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201207/
https://www.ncbi.nlm.nih.gov/pubmed/34204151
http://dx.doi.org/10.3390/s21113918
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