Distance and camera features measurements affect the detection of temperature asymmetries using infrared thermography

Machado, Álvaro; Cañada-Soriano, Mar; Jiménez-Pérez, Irene; Gil-Calvo, Marina; Carpes, Felipe P.; Pérez-Soriano, Pedro; Priego-Quesada, José Ignacio

doi:10.1080/17686733.2022.2143227

Cited by 5 publications

(6 citation statements)

References 27 publications

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“…However, the results of the temperature differences obtained for the front and right views for the different shooting distances were higher (>0.2 • C), thus indicating that the different distances selected in this study impacted the measurements, which is in agreement with a former published study where the experimental setup was comprised of focusing distances of 0.05 m and 0.15 m with a camera distance of 0.8 m [66]. It is important to bear in mind that acceptable temperature variations of less than 0.2 • C, as described in previous studies, used cameras with an advanced hardware system [64][65][66][67]. The camera used in the current study was a portable device that could be attached to a mobile phone and had a sensitivity measurement uncertainty of ±5 • C, therefore, the differences observed in the current study for the right side may also be considered as acceptable.…”

Section: Discussionsupporting

confidence: 87%

“…However, it has been reported that measurement distances between 0.2 m and 2.5 m produced small differences in temperature variations (0.2 • C), however, this recommendation was for the thermography of musculoskeletal imaging of the lower extremities [64]. In bench experiments, an image capture distance between 0.7 m and 1.5 m produced the highest inter-camera reproducibility, and shorter capture distances and cameras with superior hardware were preferable [67].…”

Section: Discussionmentioning

confidence: 99%

“…It has been recommended that for better stability, drift, and uniformity, cameras with sturdy hardware should be used [68]. The camera used in this study was from a reputed manufacturer that has previously been used for dental applications and is especially recommended for expected differences in temperature measurement greater than 0.05 • C and for its feature of portability [59,67]. The analysis software employed in this study was manufacturer recommended and therefore, concerns arising because of compatibility/sensitivity issues could be ruled out.…”

Section: Discussionmentioning

confidence: 99%

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Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Schöffauer,

Angst,

Stillhart

et al. 2023

Applied Sciences

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Thermography has not yet been validated for the screening of oral disorders and no clear guidelines or methodology for this purpose have been defined in the literature. The current pilot study was aimed as an initial step to evaluate the influence of shooting distances on the detection of the temperature asymmetries on the face for the purpose of dental thermography. Facial thermograms were taken in three views at three shooting distances for each participant. The mean temperature of the overall image and at the region of interest (ROI) were measured from the analysis software. Thirty adult volunteers participated in this study [n = 30, mean age: 25.8 ± 6.0]. The differences between the mean temperature values at the ROI for all different shooting distances within each profile view were statistically significant [Front: H(2) = 80.176, p < 0.001; Left: H(2) = 21.399, p < 0.001; Right: H(2) = 49.451, p < 0.001]. The mean ROI temperature was influenced by personal effects (p < 0.001), medications (p < 0.001), undergoing dental treatments (p < 0.001) as well as the consumption of food (p < 0.001). This study concludes that the detection of temperature asymmetries on the face in adult volunteers are affected by the capture distance as well as factors such as medication, oral-care, and alimentation. Therefore, it is advised that personal as well as medical histories are obtained in detail prior to making the facial thermograms.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Schöffauer,

Angst,

Stillhart

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

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“…The regions of interest for the unhealthy (top) and healthy (bottom) parts of the skin are cooled down and marked on the thermal image. The distance and size of the region of interest (ROI) can influence the temperature value [ 33 ]. However, in the presented approach, this factor is not as significant since two ROIs are used for comparison and they are positioned close to each other, ensuring that the camera distance is the same for both measurements.…”

Section: Resultsmentioning

confidence: 99%

Thermal Time Constant CNN-Based Spectrometry for Biomedical Applications

Strąkowska

Strzelecki

2023

Sensors

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This paper presents a novel method based on a convolutional neural network to recover thermal time constants from a temperature–time curve after thermal excitation. The thermal time constants are then used to detect the pathological states of the skin. The thermal system is modeled as a Foster Network consisting of R-C thermal elements. Each component is represented by a time constant and an amplitude that can be retrieved using the deep learning system. The presented method was verified on artificially generated training data and then tested on real, measured thermographic signals from a patient suffering from psoriasis. The results show proper estimation both in time constants and in temperature evaluation over time. The error of the recovered time constants is below 1% for noiseless input data, and it does not exceed 5% for noisy signals.

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“…However, having more pixels in an IRT does not necessarily equate to superior performance compared to the one with fewer pixels. Other parameters, such as instantaneous field of view [ 90 ], stability and drift, image uniformity [ 33 ], modulation transfer function [ 91 ], signal transfer function, noise [ 92 ], among others, can have a significant impact on the performance of an IRT.…”

Section: Discussionmentioning

confidence: 99%

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

Mazdeyasna,

Ghassemi,

Wang

2023

Sensors

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Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external temperature reference source (ETRS) for temperature compensation. The combination of an IRT and an ETRS forms a screening thermograph (ST). We investigated the effects of viewing angle (θ, 0–75°), ETRS set temperature (TETRS, 30–40 °C), ambient temperature (Tatm, 18–32 °C), relative humidity (RH, 15–80%), and working distance (d, 0.4–2.8 m). We discovered that STs exhibited higher accuracy compared to IRTs alone. Across the tested ranges of Tatm and RH, both IRTs exhibited absolute measurement errors of less than 0.97 °C, while both STs maintained absolute measurement errors of less than 0.12 °C. The optimal TETRS for EBT detection was 36–37 °C. When θ was below 30°, the two STs underestimated calibration source (CS) temperature (TCS) of less than 0.05 °C. The computer simulations showed absolute temperature differences of up to 0.28 °C and 0.04 °C between estimated and theoretical temperatures for IRTs and STs, respectively, considering d of 0.2–3.0 m, Tatm of 15–35 °C, and RH of 5–95%. The results highlight the importance of precise calibration and environmental control for reliable temperature readings and suggest proper ranges for these factors, aiming to enhance current standard documents and best practice guidelines. These insights enhance our understanding of IRT performance and their sensitivity to various factors, thereby facilitating the development of best practices for accurate EBT measurement.

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Distance and camera features measurements affect the detection of temperature asymmetries using infrared thermography

Cited by 5 publications

References 27 publications

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Optimization of Image Capture Distance for Facial Thermograms in Dentistry

Thermal Time Constant CNN-Based Spectrometry for Biomedical Applications

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

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