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Kaselimi M, Protopapadakis E, Doulamis A, Doulamis N. A review of non-invasive sensors and artificial intelligence models for diabetic foot monitoring. Front Physiol 2022; 13:924546. [PMID: 36338484 PMCID: PMC9635839 DOI: 10.3389/fphys.2022.924546] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 10/05/2022] [Indexed: 06/04/2024] Open
Abstract
Diabetic foot complications have multiple adverse effects in a person's quality of life. Yet, efficient monitoring schemes can mitigate or postpone any disorders, mainly by early detecting regions of interest. Nowadays, optical sensors and artificial intelligence (AI) tools can contribute efficiently to such monitoring processes. In this work, we provide information on the adopted imaging schemes and related optical sensors on this topic. The analysis considers both the physiology of the patients and the characteristics of the sensors. Currently, there are multiple approaches considering both visible and infrared bands (multiple ranges), most of them coupled with various AI tools. The source of the data (sensor type) can support different monitoring strategies and imposes restrictions on the AI tools that should be used with. This review provides a comprehensive literature review of AI-assisted DFU monitoring methods. The paper presents the outcomes of a large number of recently published scholarly articles. Furthermore, the paper discusses the highlights of these methods and the challenges for transferring these methods into a practical and trustworthy framework for sufficient remote management of the patients.
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Affiliation(s)
- Maria Kaselimi
- National Technical University of Athens, School of Rural, Surveying and Geoinformatics Engineering, Athens, Greece
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Pakarinen T, Oksala N, Vehkaoja A. IRlab - Platform for thermal video analysis in evaluation of peripheral thermal behavior and blood perfusion. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Mancilla RB, Tấn BP, Daul C, Martínez JG, Salas LL, Wolf D, Hernández AV. Anatomical 3D Modeling Using IR Sensors and Radiometric Processing Based on Structure from Motion: Towards a Tool for the Diabetic Foot Diagnosis. SENSORS (BASEL, SWITZERLAND) 2021; 21:3918. [PMID: 34204151 PMCID: PMC8201207 DOI: 10.3390/s21113918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/01/2021] [Accepted: 06/02/2021] [Indexed: 12/31/2022]
Abstract
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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Affiliation(s)
- Rafael Bayareh Mancilla
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Bình Phan Tấn
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Christian Daul
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Josefina Gutiérrez Martínez
- División de Ingeniería Biomédica, Instituto Nacional de Rehabilitación “Luis Guillermo Ibarra Ibarrra” (INR-LGII), Calzada México-Xochimilco 289, Coapa, Ciudad de México 14389, Mexico;
| | - Lorenzo Leija Salas
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
| | - Didier Wolf
- Centre de Recherche en Automatique de Nancy (CRAN)/CNRS, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54516 Vandœuvre-Lès-Nancy, Lorraine, France; (B.P.T.); (C.D.); (D.W.)
| | - Arturo Vera Hernández
- Departamento de Ingeniería Eléctrica/Sección de Bioelectrónica, Centro de Investigación y de Estudios Avanzados del IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, Mexico; (L.L.S.); (A.V.H.)
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