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Multimodal and multiview wound monitoring with mobile devices
(MDPI, 2021-10-01)
Along with geometric and color indicators, thermography is another valuable source of information for wound monitoring. The interaction of geometry with thermography can provide predictive indicators of wound evolution; however, existing processes are focused on the use of high-cost devices with a static configuration, which restricts the scanning of large surfaces. In this study, we propose the use of commercial devices, such as mobile devices and portable thermography, to integrate information from different wavelengths onto the surface of a 3D model. A handheld acquisition is proposed in which color images are used to create a 3D model by using Structure from Motion (SfM), and thermography is incorporated into the 3D surface through a pose estimation refinement based on optimizing the temperature correlation between multiple views. Thermal and color 3D models were successfully created for six patients with multiple views from a low-cost commercial device. The results show the successful application of the proposed methodology where thermal mapping on 3D models is not limited in the scanning area and can provide consistent information between multiple thermal camera views. Further work will focus on studying the quantitative metrics obtained by the multi-view 3D models created with the proposed methodology.
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Affine registration of thermal images of plantar feet using convolutional neural networks
(Elsevier Ltd, 2024-09-01)
The use of a thermal camera to detect abnormal plantar foot temperature changes can be an effective way to identify the early signs of diabetic foot ulceration. In this work, we performed the affine registration of the plantar foot thermal images using four models based on convolutional neural networks. The process include two parts: an affine registration model for estimating transformation parameters and a spatial transformer for getting the registered image. The performances of the four models were evaluated using the Dice similarity coefficient (DSC), Mean Square Error (MSE), and peak signal-to-noise ratio (PSNR). In the first step, Methods were applied to register the left and right feet of the same subject, called “contralateral registration” and in the second step, the methods were evaluated on a pair of images of the same subject taken in two different times (T0 and T10) using a cold stress test protocol. Results showed that the used convolutional neural networks are robust in both types of registration (contralateral and multitemporal), and they are suitable for the targeted application, with the DSC of 95% for contralateral registration and a DSC of 92% for multitemporal registration. Furthermore, a transversal clinical study was perform on diabetic patients, that classified individuals into ischemic and non-ischemic groups. The objective was to analyze the coherence between the thermal results and medical data. The mean absolute point-to-point temperature difference |ΔT| between left and right foot is lower in non-ischemic patients than in those with ischemia, with p<0.05.
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Prevention and Promotion of Wound Health Through the Ambulatory Use of Portable Thermography. Pilot Study
(Sociedad Espanola de Cirugia Plastica Reparadora y Estetica (SECPRE), 2023-10-01)
Background and objective. Chronic wounds require regular monitoring for evaluation and prevention of complications. Such assessment remains subjective, prone to error, and it is often a time-consuming and costly process for patients and public health. We propose to use three-dimensional thermographic models that can complement wound assessment. Methods. A pilot study in 6 participants where three-dimensional thermographic models were created from images obtained with low-cost portable devices. Results. The results show patterns of temperature differences that seem to be related to the behavior of the wound area. Conclusions. We observe its usefulness in providing a low-cost visualization tool and objective quantitative and qualitative indicators of the evolution of wounds, as well as the possibility of monitoring in remote areas where there is a lack of specialists, since by providing metrics, it would help in their monitoring and evaluation.
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Physico-Mechanical Properties of Alkali-Activated Based Composites Using Recycled Tire Fibers
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-02-01)
Used tires (UTs) are a global problem, especially in developing countries due to inadequate management systems. During retreading, when the worn tread is replaced, waste is generated in the form of tire fibers (TFs) and particles, which can be reused as raw materials to produce economically and environmentally low-cost prefabricated elements. Using TFs as a lightweight aggregate in nonstructural geopolymer-based elements is a sustainable valorization option. This study aims to valorize used tires by incorporating them as TFs into lightweight geopolymer mixes and analyzing their physico-mechanical, thermal, and thermography properties for building and civil engineering applications. The geopolymer is produced from a precursor (spent catalyst residue from catalytic cracking, FCC) and an alkaline activator composed of rice husk ash (RHA), sodium hydroxide, and water. The control sample's (mortar with siliceous sand, CTRLSIL) compressive strength came close to 50 MPa, while the TF mixes ranged from 32 to 3 MPa, which meet the masonry standards. The thermal conductivity and thermography analyses showed that increasing the TF content reduced the heat transmission and achieved a similar performance to expanded-clay concrete and better performance than for conventional concrete.
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