Thermography is a widely used non-contact technique in scientific research for temperature estimation and thermal analysis. However, conventional thermographic methods often suffer from significant measurement errors due to oversimplified thermal radiation models. This work addresses these limitations by contrasting conventional techniques with advanced thermography methods, introducing a spectral-directional modeling framework to enhance measurement accuracy and scientific rigor. Key contributions include the development of robust mathematical models, such as the three-component spectral-directional model, which effectively reduces measurement errors by accounting for the complexities of thermal radiation phenomena. These advancements enable accurate thermographic measurements, expanding the technique's applicability across diverse scientific fields. To the best of the author's knowledge, the application of the spectral-directional model to post-process thermal imager data represents a novel contribution to the field. Experimental results, supported by comparisons with peer-reviewed literature, highlight the transformative potential of this framework in a range of scientific applications.

The use of bismuth and its compounds in biomedicine has developed rapidly in recent years. Due to their unique properties, there are great opportunities for the development of new non-invasive strategies for the early diagnosis and effective treatment of cancers. This perspective highlights key fabrication methods to generate well-defined and clinically relevant bismuth materials of varying characteristics. On the one hand, this opens up a wide range of possibilities for unimodal and multimodal imaging. On the other hand, effective treatment strategies, which are increasingly based on combinatorial therapies, are given a great deal of attention. One of the biggest challenges remains the selective tumour targeting, whether active or passive. Here we present an overview on new developments of bismuth based materials moving forward from a simple enrichment at the tumour site via uptake by the mononuclear phagocytic system (MPS) to a more active tumour specific targeting via covalent modification with tumour-seeking molecules based on either small or antibody-derived molecules.

Here, we investigated the effectiveness of the FLIR T560 thermal imaging camera in detecting hypothermic changes associated with radiculopathy caused by spinal stenosis. This study aimed to determine whether the FLIR T560 could serve as a portable, efficient tool for diagnosing radiculopathy and its related sympathetic dysfunction in clinical practice.

A 77-year-old male had a 1-year history of neuropathic pain in the right distal lower leg, confirmed as L5 and S1 radiculopathy due to central stenosis at L4-5 and L5-S1, as shown by MRI and electrodiagnostic studies. The FLIR T560 recorded thermal images in an insulated room, revealing a significantly lower surface temperature (approximately 1.0°C difference) on the lateral and posterior right distal lower leg and right toes compared with the left side. By referencing the color map and scale, we estimated that the relative temperature difference between corresponding areas was approximately 1.0°C.

L5 and S1 radiculopathy due to central stenosis at L4-5 and L5-S1.

A transforaminal epidural steroid injection targeting the right L5 and S1 nerve roots was conducted.

The patient's pain improved significantly.

The FLIR T560 camera offers a portable and convenient alternative to traditional digital infrared thermographic imaging, allowing real-time thermal imaging in a clinical setting without the need for additional equipment. Our case report suggests that the FLIR T560 is a valuable tool for detecting sympathetic dysfunction associated with radiculopathy. Further studies with larger patient populations are recommended to validate its clinical utility.

Monitoring the training load is crucial in sports science research, as it provides scientific evidence for assessing training effects, optimizing athletic performance, and preventing overtraining by quantifying both external and internal loads. Although traditional monitoring methods have made significant progress, infrared thermography (IRT) technology, with its non-contact, real-time, and non-invasive characteristics, is gradually emerging as an effective tool for evaluating the relationship between the training load and physiological responses. This study evaluated 31 healthy male adults (age 21.9 ± 2.7 years, weight 75 ± 8.26 kg, and training duration 240 ± 65 min/week) performing incremental exhaustive exercise on a cycle ergometer (with a 60W starting load, increasing by 20W per minute). Entropy analysis was used to quantitatively assess the surface radiation patterns of regions of interest (forehead, chest, and abdomen) obtained through thermal imaging. Compared to baseline, significant differences in the surface radiation patterns of the regions of interest were observed at the point of exhaustion (p ≤ 0.01). Correlation analysis revealed strong associations between the external load, oxygen consumption, and chest temperature entropy (r = 0.973 and 0.980). Cluster analysis of the chest entropy, external load, and oxygen consumption showed a non-linear increasing trend in their inter-relationships. Further individual analysis demonstrated positive correlations between the percentage increase in the chest entropy and both the external load (r = 0.70-0.98) and oxygen consumption (r = 0.65-0.97). Entropy analysis offers a new approach for quantitatively assessing surface radiation patterns from infrared thermography, and reveals the coupling relationship between thermoregulation and metabolic responses during exercise.

Thermography is a noninvasive method to identify patients at risk of diabetic foot ulcers. In this study, we employed thermography and deep learning to stratify patients with diabetes at risk of developing foot ulcers.

We prospectively recorded clinical data and plantar thermograms for adult patients with diabetes who underwent diabetic foot screening. A total of 153 thermal images were analyzed using a deep learning algorithm to determine the risk of diabetic foot ulcers. The neural network was trained using a balanced dataset consisting of 98 thermal images (49 normal and 49 abnormal), with 80% allocated for training and 20% for validation. The trained model was then validated on a separate testing dataset consisting of 55 thermal images (42 normal and 13 abnormal). The neural network was trained to prioritize higher sensitivity in identifying at-risk feet for screening purposes.

Participants had a mean age of 63.1 ± 12.6 years (52.3% female), and 62.1% had been diagnosed with diabetes for more than 10 years. The average body mass index was 27.5 ± 5.6 kg/m2. Of the thermal images, 91 were classified as category 0 and 62 as categories 1 to 3, according to the diabetic foot risk classification system of the International Working Group on the Diabetic Foot. Using five-fold cross-validation, the neural network model achieved an overall accuracy of 71.8 ± 4.9%, a sensitivity of 81.2 ± 10.0%, and a specificity of 64.0 ± 7.4%. Additionally, the Matthews correlation coefficient was 0.46 ± 0.08.

These results suggest that thermography combined with deep learning could be developed for screening purposes to stratify patients at risk of developing diabetic foot ulcers.

several authors have documented variations in local temperature in both horses and dogs presenting acute intervertebral disc extrusion (IVDE) along the entire spinal column. However, none have demonstrated distinct temperature differences between healthy animals and those with IVDE. A retrospective study was conducted to assess the efficacy of thermography at evaluating local temperature and thermal patterns in healthy dogs as well in those with IVDE across the T11-L3 area.

the study included 20 healthy dogs and 32 dogs with IVDE. For both groups of dogs, the thoracolumbar region was trimmed and, subsequently, scanned using the Flir E50 thermography device. The Flir Tool software was used to analyze three designated areas (Bx1, Bx2, Bx3) within the thoracolumbar region by comparing the average temperature of the minimum, maximum, and mean temperature recordings between the two groups.

the thermal pattern and the local temperature of the thoracolumbar area present differences between healthy dogs and those with IVDE.

we recommend thermographic scanning of the thoracolumbar area to find differences in local temperature between healthy dogs and those with intervertebral disc extrusion. Further investigations are required to differentiate between disc extrusion that exhibits lateralization to the right or left.

This study aim was to analyze the joint temperature of patients affected by bilateral knee osteoarthritis (OA) using infrared thermography to investigate whether thermographic imaging patterns are influenced by the severity of symptoms and joint degeneration.

Sixty-sixpatients ranging from 43 to 78 years old (63.3 ± 8.8 years) with bilateral knee OA and one symptomatic knee were enrolled. Thermograms of the two knees were captured using a thermographic camera FLIR T1020 and analyzed with the ResearchIR software to calculate the temperature of the overall knee and the four regions of interest (ROIs): patella, suprapatellar, medial, and lateral areas.

The temperature of knees affected by OA was influenced by joint degeneration level and symptoms: patients with higher OA grade in the symptomatic knees presented higher total knee temperatures compared to the asymptomatic ones (p = 0.002), as well as in the patellar (p = 0.005), lateral (p = 0.002), and medial (p = 0.001) areas. On the other hand, patients with the same OA level in the two knees presented a higher temperature in the symptomatic knee only in the medial area (p = 0.037). Symptomatic knees demonstrated a different pattern compared to asymptomatic knees, with the medial area presenting the highest temperature changes (p = 0.020). Patients reporting prevalent pain in the lateral knee area presented higher differences in total knee temperature (0.7 ± 0.7 °C) than patients with pain in the medial area (0.1 ± 0.5 °C) (p = 0.023).

The temperature of knees affected by OA is influenced by the degree of joint degeneration and by the presence of symptoms, with higher temperatures found in symptomatic joints, especially with prevalent lateral knee pain, and in more severe OA. Symptomatic knees demonstrated a different pattern compared to asymptomatic knees, with the medial area presenting the highest temperature changes.

Pregnancy comprises a period of 41 weeks, in which the female body undergoes several physiological, hormonal and anatomical changes that can generate changes in skin temperature.

To describe the thermal profile of pregnant women during the first, second and third trimester of pregnancy.

This is a cross-sectional observational study. A total of 104 women participated, divided into three groups: first trimester group (1 TG, n = 25), second trimester group (2 TG, n = 27), third trimester group (3 TG, n = 26), and non-pregnant control group (CG, n = 26). All underwent thermographic evaluations using a thermographic camera model E54-EST, and anthropometric measurements of abdominal circumference and diastasis.

It was observed that the average skin temperature of pregnant women in the first trimester is higher than the average skin temperature of pregnant women in the third trimester of pregnancy (P < 0.05); the abdominal temperature of pregnant women in the first trimester tends to be higher than that of pregnant women in the second and third trimesters (P < 0.05); and the breast skin temperature of pregnant women is higher than that of non-pregnant women (P < 0.05). Furthermore, there is a tendency for negative correlations between the average skin temperature and the temperature of the abdominal and diastasis regions with fetal development measures.

It is generally observed that there are differences in the skin temperatures of regions such as the breast between pregnant women and non-pregnant women, as well as a tendency for higher abdominal temperatures in pregnant women in the first trimester compared to those in the third trimester.

Background: Ultrasound-induced thermal strain imaging (US-TSI) is a promising ultrasound imaging modality that has been demonstrated in preclinical studies to identify a lipid-rich necrotic core of an atherosclerotic plaque. However, human physiological motion, e.g., cardiac pulsation, poses challenges in implementing US-TSI applications, where achieving a millisecond-level temperature rise by delivering acoustic energy from a compact US-TSI probe is a key requirement. This study aims to develop a transient ultrasound heating and thermocouple monitoring technique at the millisecond level for US-TSI applications. Methods: We designed, prototyped, and characterized a novel US-TSI probe that includes a high-power, 3.5 MHz heating transducer with symmetrical dual 1D concave array. Additionally, millisecond-level temperature monitoring was demonstrated with fast-response thermocouples in laser- and ultrasound- induced thermal tests. Subsequently, we demonstrated the prototyped US-TSI probe can produce a desired temperature rise in a millisecond-short time window in vitro phantom and in vivo animal tests. Results: The prototyped US-TSI probe delivered zero-to-peak acoustic pressure up to 6.2 MPa with a 90 VPP input voltage. Both laser- and ultrasound- induced thermal tests verified that the selected thermocouples can monitor temperature change within 50 ms. The fast-response thermocouple confirmed the transient heating ability of the US-TSI probe, achieving a 3.9 °C temperature rise after a 25 ms heating duration (50% duty cycle) in the gel phantom and a 2.0 °C temperature rise after a 50 ms heating duration (50% duty cycle) in a pig model. Conclusions: We successfully demonstrated a millisecond-level transient heating and temperature monitoring technique utilizing the novel US-TSI probe and fast-response thermocouples. The reported transient ultrasound heating and thermocouple monitoring technique is promising for future in vivo human subject studies in US-TSI or other ultrasound-related thermal investigations.

The precise measurement of cell temperature and an in-depth understanding of thermogenic processes are critical in unraveling the complexities of cellular metabolism and its implications for health and disease. This review focuses on the mechanisms of local temperature generation within cells and the array of methods developed for accurate temperature assessment. The contact and noncontact techniques are introduced, including infrared thermography, fluorescence thermometry, and other innovative approaches to localized temperature measurement. The role of thermogenesis in cellular metabolism, highlighting the integral function of temperature regulation in cellular processes, environmental adaptation, and the implications of thermogenic dysregulation in diseases such as metabolic disorders and cancer are further discussed. The challenges and limitations in this field are critically analyzed while technological advancements and future directions are proposed to overcome these barriers. This review aims to provide a consolidated resource for current methodologies, stimulate discussion on the limitations and challenges, and inspire future innovations in the study of cellular thermodynamics.

This study aimed to investigate the incidence of subclinical mastitis (SCM), the implicated pathogens, and their impact on milk quality in dairy sheep in Greece. Furthermore, we preliminarily evaluated infrared thermography and the application of AI tools for the early, non-invasive diagnosis of relevant cases. In total, 660 milk samples and over 2000 infrared thermography images were obtained from 330 phenotypically healthy ewes. Microbiological investigations, a somatic cell count (SCC), and milk chemical analyses were performed. Infrared images were analyzed using the FLIR Research Studio software (version 3.0.1). The You Only Look Once version 8 (YOLOv8) algorithm was employed for the automatic detection of the udder's region of interest. A total of 157 mammary glands with SCM were identified in 122/330 ewes (37.0%). The most prevalent pathogen was staphylococci (136/160, 86.6%). Considerable resistance was detected to tetracycline (29.7%), ampicillin (28.6%), and sulfamethoxazole-trimethoprim (23.6%). SCM correlated with high total mesophilic count (TMC) values and decreased milk fat, lactose, and protein content. A statistically significant variation (p < 0.001) was identified in the unilateral SCM cases by evaluating the mean temperatures of the udder region between the teats in the thermal images. Finally, the YOLOv8 algorithm was employed for the automatic detection of the udder's region of interest (ROI), achieving 84% accuracy in defining the ROI in this preliminary evaluation. This demonstrates the potential of infrared thermography combined with AI tools for the diagnosis of ovine SCM. Nonetheless, more extensive sampling is essential to optimize this diagnostic approach.

Skin cancer is a growing global concern, with cases steadily rising. Typically, malignant moles are identified through visual inspection, using dermatoscopy and patient history. Active thermography has emerged as an effective method to distinguish between malignant and benign lesions. Our previous research showed that spatio-temporal features can be extracted from suspicious lesions to accurately determine malignancy, which was applied in a distance-based classifier. In this study, we build on that foundation by introducing a set of novel spatial and temporal features that enhance classification accuracy and can be integrated into any machine learning approach. These features were implemented in a support-vector machine classifier to detect malignancy. Notably, our method addresses a common limitation in existing approaches-manual lesion selection-by automating the process using a U-Net convolutional neural network. We validated our system by comparing U-Net's performance with expert dermatologist segmentations, achieving a 17% improvement in the Jaccard index over a semi-automatic algorithm. The detection algorithm relies on accurate lesion segmentation, and its performance was evaluated across four segmentation techniques. At an 85% sensitivity threshold, expert segmentation provided the highest specificity at 87.62%, while non-expert and U-Net segmentations achieved comparable results of 69.63% and 68.80%, respectively. Semi-automatic segmentation lagged behind at 64.45%. This automated detection system performs comparably to high-accuracy methods while offering a more standardized and efficient solution. The proposed automatic system achieves 3% higher accuracy compared to the ResNet152V2 network when processing low-quality images obtained in a clinical setting.

Introduction: Clavicle fractures are among the most common in children, typically treated conservatively, with standard radiographs used to diagnose and monitor healing. Recently, infrared thermography (IRT) has been proposed as an alternative method for fracture detection, but no study has correlated the temperature changes during callus formation. Materials and Methods: Children aged 4-18 with X-ray-diagnosed clavicle fractures were included in the study. IRT measured temperatures above the fracture and contralateral healthy side on the 1st, 4th, 8th, 15th, and 22nd day after the injury. Along with IRT, an ultrasound was used to assess callus formation. Results: The study included 27 patients with an average age of 12.4 years, mostly boys. The left side was more often affected than the right side (33%). We found a correlation between callus formation and the ∆T. A maximum temperature difference of an average of 0.7 °C was noted during the proliferative phase of callus formation. After the formation of the fibrocartilaginous callus (4th to 8th day), the temperature above the fracture declined until it was equal (22nd day) to that of the healthy side. The average temperature difference between the broken and the healthy sides was statistically significant on the 4th and 8th days (during callus formation). Conclusions: The increased skin temperature above the fracture correlates with the inflammatory phase of bone healing. After the callus is visible on ultrasound, the temperature linearly drops with no statistical difference between the injured and the healthy sides. The standard protocol for clavicle fracture treatment typically involves using X-rays to assess callus formation during follow-up. IRT has shown potential in diagnosing callus formation in children with clavicle fractures, potentially reducing the need for traditional X-rays.

Breast cancer remains a leading cause of cancer mortality worldwide, with early detection crucial for improving outcomes. This systematic review evaluates recent advances in portable non-invasive technologies for early breast cancer detection, assessing their methods, performance, and potential for clinical implementation. A comprehensive literature search was conducted across major databases for relevant studies published between 2015 and 2024. Data on technology types, detection methods, and diagnostic performance were extracted and synthesized from 41 included studies. The review examined microwave imaging, electrical impedance tomography (EIT), thermography, bioimpedance spectroscopy (BIS), and pressure sensing technologies. Microwave imaging and EIT showed the most promise, with some studies reporting sensitivities and specificities over 90 %. However, most technologies are still in early stages of development with limited large-scale clinical validation. These innovations could complement existing gold standards, potentially improving screening rates and outcomes, especially in underserved populations, whiles decreasing screening waiting times in developed countries. Further research is therefore needed to validate their clinical efficacy, address implementation challenges, and assess their impact on patient outcomes before widespread adoption can be recommended.

Thermographic imaging is a technique to measure infrared radiation to report temperature and has been used in prior research to assess sexual arousal by measuring genital temperature. We hypothesized this can be used quantitatively to assess erectile function. We conducted an observational clinical trial of this technique by performing thermographic imaging in the flaccid and erect state and compared these values with hemodynamic measurements performed by penile Doppler/duplex ultrasound (PDDU). We also hypothesized that in men with Peyronie's disease (PD), the plaque would be visible on thermographic imaging and took thermographic measurements in this area for patients with PD. Any man scheduled to undergo PDDU in our urology clinic was approached for recruitment. PDDU was performed by one of two experienced urologists. We recruited 30 men for this study. Seven of these men had PD. The change in measured temperature between flaccid and erect states correlated significantly with the peak systolic velocity r = 0.46 (p = 0.025). In the seven men with PD the mean change in temperature of the plaque was +0.9 °C versus +2.1 °C in the normal penis (p = 0.28). Thermographic imaging shows a significant correlation with objective hemodynamic measurements on PDDU.

Excessive seepage significantly affects the stability of levees during flood seasons. Recently, infrared thermal imaging technology has been proposed to detect the seepage leakage of levees for its simplicity, high efficiency and non-contact. However, previous studies mainly focused on theoretical and laboratory tests to verify its effect, which involve many assumptions and simplification. This paper aims to study the practical application effects of infrared thermal imaging technology on levee leakage detection. A typical embankment in Xiangyin County, Hunan Province is selected as the studied area, where a specific point containing water is considered as the potential leakage point. Then, DJI M300RTK UAV equipped with Zenith H20T gimbal is adopted to collect the visible and infrared images of the embankment's leaking point. The visible and infrared image data collected at different times and at different measurement heights are analyzed to investigate the detection accuracy of infrared thermal imaging technology. Results show that the infrared thermal imaging technology can accurately identify the potential seepage leakage point of levees. Compared with the visible light recognition method, the infrared thermal imaging technology can identify the location and scope of leakage hazards more clearly and accurately at night. During the daytime, infrared detection is less effective than visible light method. Moreover, the measurement altitude between the drone and the target leakage points significantly affects the detection accuracy of infrared thermal imaging technology.

Although the measurement of tooth quality is necessary for precise prediction of caries formation, typical measurement methods include tooth-hardness measurements and absorption spectroscopy, which generally use infrared light irradiation. These methods are destructive or invasive, and obtaining two-dimensional information in the oral cavity is difficult. Mid-infrared emissions from the surface of an object reflect intrinsic vibrations of molecules in the object. In this study, a mid-infrared passive spectroscopic imaging system was developed using an inexpensive uncooled microbolometer array sensor with an optimized multi-slit, which eliminated the cancellation of interference intensities between two adjacent emission points, to obtain two-dimensional information from an object without external infrared light irradiation. First, the feasibility of obtaining two-dimensional information on tooth quality using the proposed system was examined, and emission spectra attributed to phosphate ions in hydroxyapatite (HAp), the main component of enamel, were successfully obtained from bovine teeth. Further, the hardness of bovine teeth was measured, and a correlation (R2 = 0.8067) between the Vickers hardness and peak area ratio of phosphate ions assigned to the crystalline and amorphous phases of a tooth was established. Additionally, tooth-hardness visualization in a non-contact manner was demonstrated as two-dimensional information using the obtained regression equation.

Among the health issues of major concern in dairy ruminants, mastitis stands out as being associated with considerable losses in productivity and compromised animal health and welfare. Currently, the available methods for the early detection of mastitis are either inaccurate, requiring further validation, or expensive and labor intensive. Moreover, most of them cannot be applied at the point of care. Infrared thermography (IRT) is a rapid, non-invasive technology that can be used in situ to measure udder temperature and identify variations and inconsistencies thereof, serving as a benchmarking tool for the assessment of udders' physiological and/or health status. Despite the numerous applications in livestock farming, IRT is still underexploited due to the lack of standardized operation procedures and significant gaps regarding the optimum settings of the thermal cameras, which are currently exploited on a case-specific basis. Therefore, the objective of this review paper was twofold: first, to provide the state of knowledge on the applications of IRT for the assessment of udder health status in dairy ruminants, and second, to summarize and discuss the major strengths and weaknesses of IRT application at the point of care, as well as future challenges and opportunities of its extensive adoption for the diagnosis of udder health status and control of mastitis at the animal and herd levels.

To assess the influence of two conventional and one adapted cheek and lip retractors and three emissivity setting values on intraoral infrared thermography (IT) temperature values.

The sample was composed by 50 volunteers. Three cheek and lip retractors were tested: Group 1-flex retractor (FR); Group 2-FR adapted with Styrofoam; Group 3-U-type retractor (UR) for cheek and lip. All thermograms were acquired using FLIR T650 infrared camera. A set of three thermograms in frontal norm were acquired for each lip and cheek retractor at 0.91, 0.96, and 0.98ε, with an interval of 15 min between each set of images to avoid thermal interference. All images were assessed by two observers. The ROIs' mean temperature of the four upper incisors was recorded. Two-way ANOVA and Sidak post-test were used for data assessment with a significance level of 5%.

Group 3 showed higher mean temperature than Groups 1 and 2 at all emissivity settings for all assessed teeth (P < .05). 0.91ε showed higher temperature than 0.96ε and 0.98ε for all assessed variables (P < .01). Contralateral teeth assessed using Group 3 at 0.91ε showed statistical differences between each other (P < .05). No statistical difference was observed between contralateral teeth assessed using Groups 1 and 2 at 0.96ε and 0.98ε (P > .05).

The choice of cheek and lip retractor and emissivity setting can interfere on intraoral IT temperature values. U-type cheek and lip retractor and 0.91ε setting should not be used for IT image acquisition when assessing dental tissues.

The use of lanthanide luminescence has advanced the field of remote temperature sensing. Luminescence intensity ratio methods relying on emission from two thermally coupled energy levels are popular but suffer from a limited temperature range. Here, we present a versatile luminescent thermometer: Ba(Sr)FBr(Cl):Sm2+. The Sm2+ ion benefits from multiple thermally coupled excited states to extend the temperature range and has strong parity-allowed 4f6→4f55d1 absorption to increase brightness. We conduct a comparative analysis of the temperature sensing performance of Sm2+ in BaFBr, BaFCl, SrFBr, and SrFCl and address the role of concentration, host, and Boltzmann equilibration. Different thermal coupling schemes, 5D1-5D0 and 4f55d1-5D0, and temperature-dependent lifetimes enable accurate sensing between 350 and 800 kelvin. Differences in 4f55d1-5D0 energy gap allows optimization for a temperature range of interest. This type of Sm2+-based thermometer holds great potential for temperature monitoring in the wide and relevant range up to 500°C.

Infrared thermography is considered a useful technique for diagnosing several skin pathologies but it has not been widely adopted mainly due to its high cost. Here, we investigate the feasibility of using low-cost infrared cameras with microbolometer technology for detecting skin cancer. For this purpose, we collected infrared data from volunteer subjects using a high-cost/high-quality infrared camera. We propose a degradation model to assess the use of lower-cost imagers in such a task. The degradation model was validated by mimicking video acquisition with the low-cost cameras, using data originally captured with a medium-cost camera. The outcome of the proposed model was then compared with the infrared video obtained with actual cameras, achieving an average Pearson correlation coefficient of more than 0.9271. Therefore, the model successfully transfers the behavior of cameras with poorer characteristics to videos acquired with higher-quality cameras. Using the proposed model, we simulated the acquisition of patient data with three different lower-cost cameras, namely, Xenics Gobi-640, Opgal Therm-App, and Seek Thermal CompactPRO. The degraded data were used to evaluate the performance of a skin cancer detection algorithm. The Xenics and Opgal cameras achieved accuracies of 84.33% and 84.20%, respectively, and sensitivities of 83.03% and 83.23%, respectively. These values closely matched those from the non-degraded data, indicating that employing these lower-cost cameras is appropriate for skin cancer detection. The Seek camera achieved an accuracy of 82.13% and a sensitivity of 79.77%. Based on these results, we conclude that this camera is appropriate for less critical applications.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Thermal imaging combined with advanced image-processing and machine learning analysis accurately classified disease status in a study on mice; this study aimed to develop this tool for humans. This prospective study included 46 patients who underwent liver biopsy. Liver thermal imaging was performed on the same day as liver biopsy. We developed an image-processing algorithm that measured the relative spatial thermal variation across the skin covering the liver. The texture parameters obtained from the thermal images were input into the machine learning algorithm. Patients were diagnosed with MASLD and stratified according to nonalcoholic fatty liver disease activity score (NAS) and fibrosis stage using the METAVIR score. Twenty-one of 46 patients were diagnosed with MASLD. Using thermal imaging followed by processing, detection accuracy for patients with NAS >4 was 0.72.

Infrared thermography (IRT) is a well-known imaging technique that provides a non-invasive displaying of the ocular surface temperature distribution. Currently, compact smartphone-based IRT devices, as well as special software for processing thermal images, have become available. The study aimed to determine the possible use of smartphone-based IRT devices for real-time ocular surface thermal imaging. This study involved 32 healthy individuals (64 eyes); 10 patients (10 eyes) with proliferative diabetic retinopathy (PDR) and absolute glaucoma; 10 patients (10 eyes) with PDR, who underwent vitreoretinal surgery. In all cases, simultaneous ocular surface IRT of both eyes was performed. In healthy individuals, the ocular surface temperature (OST) averaged 34.6 ± 0.8 °C and did not differ substantially between the paired eyes, in different age groups, and after pupil dilation. In our study, high intraocular pressure was accompanied by a decrease in OST in all cases. After vitreoretinal surgery in cases with confirmed subclinical inflammation, the OST was higher than the baseline and differed from that of the paired eye by more than 1.0 °C. These results highlight that smartphone-based IRT imaging could be useful for the non-invasive detection of OST asymmetry between paired eyes due to increased intraocular pressure or subclinical inflammation.

Thermal imaging can be used for the non-invasive detection of blood vessels of the skin. However, mapping the results to the patient currently lacks user-friendliness. Augmented reality may provide a useful tool to superimpose thermal information on the patient.

A system to support planning in reconstructive surgery using a thermal camera was designed. The obtained information was superimposed on the physical object using a Microsoft HoloLens. An RGB, depth, and thermal camera were combined to capture a scene of different modalities and reconstruct a virtual scene in real time. To register the different cameras and the AR device, an active calibration target was developed and evaluated. A Vuforia marker was used to register the hologram in the virtual space. The accuracy of the projected hologram was evaluated in a laboratory setting with participants by measuring the error between the physical object and the hologram.

The AR-based system was evaluated by 21 participants in a laboratory setting. The mean projection error is 10.3 ± 9.4 mm. The system is able to stream a three-dimensional scene with augmented thermal information in real time at 5 frames per second. The active calibration target can be used independently of the environment.

The calibration target provides an easy-to-use method for the registration of cameras capturing the visible to long-infrared spectral range. The inside-out tracking of the HoloLens in combination with a Vuforia marker is not accurate enough for the intended clinical use.

Infrared thermography is gaining relevance in breast cancer assessment. For this purpose, breast segmentation in thermograms is an important task for performing automatic image analysis and detecting possible temperature changes that indicate the presence of malignancy. However, it is not a simple task since the breast limit borders, especially the top borders, often have low contrast, making it difficult to isolate the breast area. Several algorithms have been proposed for breast segmentation, but these highly depend on the contrast at the lower breast borders and on filtering algorithms to remove false edges. This work focuses on taking advantage of the distinctive inframammary shape to simplify the definition of the lower breast border, regardless of the contrast level, which indeed also provides a strong anatomical reference to support the definition of the poorly marked upper boundary of the breasts, which has been one of the major challenges in the literature. In order to demonstrate viability of the proposed technique for an automatic breast segmentation, we applied it to a database with 180 thermograms and compared their results with those reported by others in the literature. We found that our approach achieved a high performance, in terms of Intersection over Union of 0.934, even higher than that reported by artificial intelligence algorithms. The performance is invariant to breast sizes and thermal contrast of the images.

To identify the sensitivity, specificity, and overall diagnostic accuracy of infrared thermography in diagnosing lumbosacral radicular pain.

Patients sequentially presenting with lower extremity pain were enrolled. A clinical certainty score ranging from 0 to 10 was used to assess the likelihood of lumbosacral radicular pain, with higher scores indicating higher likelihood. Infrared Thermography scans were performed and the temperature difference (ΔT) was calculated as ΔT = T1 - T2, where T2 represents the skin temperature of the most painful area on the affected limb and T1 represents the skin temperature of the same area on the unaffected limb. Upon discharge from the hospital, two independent doctors diagnosed lumbosacral radicular pain based on intraoperative findings, surgical effectiveness, and medical records.

A total of 162 patients were included in the study, with the adjudicated golden standard diagnosis revealing that 101 (62%) patients had lumbosacral radicular pain, while the lower extremity pain in 61 patients was attributed to other diseases. The optimal diagnostic value for ΔT was identified to fall between 0.8℃ and 2.2℃, with a corresponding diagnostic accuracy, sensitivity, and specificity of 80%, 89%, and 66% respectively. The diagnostic accuracy, sensitivity, and specificity for the clinical certainty score were reported as 69%, 62%, and 79% respectively. Combining the clinical certainty score with ΔT yielded a diagnostic accuracy, sensitivity, and specificity of 84%, 77%, and 88% respectively.

Infrared thermography proves to be a highly sensitive tool for diagnosing lumbosacral radicular pain. It offers additional diagnostic value in cases where general clinical evaluation may not provide conclusive results.

ChiCTR2300078786, 19/22/2023.

Protocol description for renal perfusion study using thermographic technology and description of the thermographic and clinical behavior of the transplanted kidneys before and after unclamping.

Infrared thermographic images of renal grafts are obtained before kidney reperfusion, 10 min after and just before closing the surgical wound. Thermographic data is evaluated together with the type of graft and donor, cold ischemia time, hypovascularized areas determined by the surgeon during surgical intervention, alterations in vascular flow in postoperative echo-Doppler, time at the beginning of graft function and serum creatinine monitoring during postoperative follow-up.

17 grafts were studied. The mean temperature of the grafts before reperfusion, 10 min after and at the end of the surgery were 18.7 °C (SD 6.27), 32.36 °C (SD1.47) and 32.07 °C (SD1.78) respectively. 4 grafts presented hypoperfused areas after reperfusion. These areas presented a lower temperature compared to the well perfused parenchyma surface using thermographic images.

The study of the usefulness and applicability of thermography can allow the development of tools that provide additional objective information on organ perfusion in real time and non-invasive manner. Our protocol and initial results can contribute to provide new evidence. Further analyses should be developed to shed light on the role of this technology.

This review aims to explore recent advancements in optical imaging techniques for monitoring the viability of Deep Inferior Epigastric Perforator (DIEP) flap reconstruction. The objectives include highlighting the principles, applications, and clinical utility of optical imaging modalities such as near-infrared spectroscopy (NIRS), indocyanine green (ICG) fluorescence angiography, laser speckle contrast imaging (LSCI), hyperspectral imaging (HSI), dynamic infrared thermography (DIRT), and short-wave infrared thermography (SWIR) in assessing tissue perfusion and oxygenation. Additionally, this review aims to discuss the potential of these techniques in enhancing surgical outcomes by enabling timely intervention in cases of compromised flap perfusion.

A comprehensive literature review was conducted to identify studies focusing on optical imaging techniques for monitoring DIEP flap viability. We searched PubMed, MEDLINE, and relevant databases, including Google Scholar, Web of Science, Scopus, PsycINFO, IEEE Xplore, and ProQuest Dissertations & Theses, among others, using specific keywords related to optical imaging, DIEP flap reconstruction, tissue perfusion, and surgical outcomes. This extensive search ensured we gathered comprehensive data for our analysis. Articles discussing the principles, applications, and clinical use of NIRS, ICG fluorescence angiography, LSCI, HSI, DIRT, and SWIR in DIEP flap monitoring were selected for inclusion. Data regarding the techniques' effectiveness, advantages, limitations, and potential impact on surgical decision-making were extracted and synthesized.

Optical imaging modalities, including NIRS, ICG fluorescence angiography, LSCI, HSI, DIRT, and SWIR offer a non- or minimal-invasive, real-time assessment of tissue perfusion and oxygenation in DIEP flap reconstruction. These techniques provide objective and quantitative data, enabling surgeons to monitor flap viability accurately. Studies have demonstrated the effectiveness of optical imaging in detecting compromised perfusion and facilitating timely intervention, thereby reducing the risk of flap complications such as partial or total loss. Furthermore, optical imaging modalities have shown promise in improving surgical outcomes by guiding intraoperative decision-making and optimizing patient care.

Recent advancements in optical imaging techniques present valuable tools for monitoring the viability of DIEP flap reconstruction. NIRS, ICG fluorescence angiography, LSCI, HSI, DIRT, and SWIR offer a non- or minimal-invasive, real-time assessment of tissue perfusion and oxygenation, enabling accurate evaluation of flap viability. These modalities have the potential to enhance surgical outcomes by facilitating timely intervention in cases of compromised perfusion, thereby reducing the risk of flap complications. Incorporating optical imaging into clinical practice can provide surgeons with objective and quantitative data, assisting in informed decision-making for optimal patient care in DIEP flap reconstruction surgeries.

Existing mid-infrared thermographic cameras rely on a stack of refractive lenses, resulting in bulky and heavy imaging systems that restrict their broader utility. Here, we demonstrate a lightweight metalens-based thermographic camera (MTC) enabled by a single 0.5-mm-thick, 3.7-g-weight, flat, and mass-producible metalens. The large aperture size (5 cm) of our metalens, when combined with an uncooled focal plane array, enables thermal imaging at distances of tens of meters. By computationally removing the veiling glare, our MTC realizes the temperature mapping with an inaccuracy of less than ±0.7% within the range of 35° to 700°C and shows exceptional environmental adaptability. Furthermore, by using intelligent algorithms and spectral filtering, our uncooled MTC enables visualization and quantification of the SF6 gas leakage at a long distance of 5 m, with a remarkable minimum detectable leak rate of 0.2 sccm. Our work opens the door to the lightweight and multifunctional intelligent thermal imaging systems.

The liveliness of a human potentially depends on his/her smooth movability. To accomplish the work of daily life, the joints of the body need to be healthy. However, the occurrence of Rheumatoid arthritis and Osteoarthritis has a significant prevalence towards the immovability of humankind. Rheumatoid arthritis (RA) and Osteoarthritis (OA) mostly affect the joints of the hand and knee which result in lifelong pain, inability to climb, walk, etc. In the early stages, these diseases attack the synovial membrane and synovial fluid, and further it destroys the soft tissues and bone structure. By early diagnosis, we can start the treatment in the early stage which may cure these diseases with such extreme consequences. As per clinical studies of previous literature, it is observed that synovial fluid imbalance appears in the early stage of such diseases and Hyaluronic Acid (HA) concentration also decreases for that. Therefore, estimation of HA is a significant key to arthritis disease classification and grading. In this paper, we proposed a hybrid framework for classification of arthritic knee joints based on the analysis of the discontinuous appearances of the HA concentration using infrared imaging technology. To meet up the specific necessities, firstly we have proposed a modified K-Means clustering algorithm for extraction of the region of interest (ROI) i.e., the knee joint surface. Secondly, a mathematical formulation is proposed to calculate the concentration of HA from the segmented ROIs. This experimental process was implemented on the publicly available IR (Infrared) Knee Joint Dataset and for further evaluation of the novelty of mathematical formulation, we have extended the proposed work to the classification of healthy and arthritis affected knee joints depending on significant discriminative characteristics of the HA concentration with respect to the existing significant imaging features. Experimental results and analysis demonstrates that concentration of HA has the dominant potential for classifying healthy and arthritic knee joints using infrared holistic images. Our experimental analysis reveals that estimation and combination of the HA concentration features with conventional handcrafted and deep features increases the classification performance with an average accuracy of 91% and 97.22% respectively as compared to the each individual feature sets.

Knee degenerative processes, such as osteoarthritis, are disabling. An early intervention is generally more effective making important a timely diagnosis. A pre-diagnosis tool could be the thermal camera that allows the detection of joint inflammation. Consequently, the objective of the present study was to evaluate the literature and propose a thermal attention threshold for infrared thermography data in people with knee osteoarthritis.

four electronic databases were searched with specific keywords until the 25th of March 2024. Only original articles about joint inflammation due to osteoarthritis evaluated through digital infrared thermal images were included. A quality assessment analysis was performed. The attention threshold was extracted through the median of the extracted data. The findings were narratively discussed.

A total of 9 studies have been included after the eligibility criteria selection. The studies presented some differences in terms of acquisition protocol, thermal imaging camera, data extrapolation, and analysis. Despite these differences, the studies presented similar thermal data.

A knee thermography of or above 31.3 °C could indicate osteoarthritis, highlighting the necessity of further, more specific, and accurate analysis.

External validation is crucial in developing reliable machine learning models. This study aimed to validate three novel indices-Thermographic Joint Inflammation Score (ThermoJIS), Thermographic Disease Activity Index (ThermoDAI), and Thermographic Disease Activity Index-C-reactive protein (ThermoDAI-CRP)-based on hand thermography and machine learning to assess joint inflammation and disease activity in rheumatoid arthritis (RA) patients. A 12-week prospective observational study was conducted with 77 RA patients recruited from rheumatology departments of three hospitals. During routine care visits, indices were obtained at baseline and week 12 visits using a pre-trained machine learning model. The performance of these indices was assessed cross-sectionally and longitudinally using correlation coefficients, the area under the receiver operating curve (AUROC), sensitivity, specificity, and positive and negative predictive values. ThermoDAI and ThermoDAI-CRP correlated with CDAI, SDAI, and DAS28-CRP cross-sectionally (ρ = 0.81; ρ = 0.83; ρ = 0.78) and longitudinally (ρ = 0.55; ρ = 0.61; ρ = 0.60), all p < 0.001. ThermoDAI and ThermoDAI-CRP also outperformed Patient Global Assessment (PGA) and PGA + C-reactive protein (CRP) in detecting changes in 28-swollen joint counts (SJC28). ThermoJIS had an AUROC of 0.67 (95% CI, 0.58 to 0.76) for detecting patients with swollen joints and effectively identified patients transitioning from SJC28 > 1 at baseline visit to SJC28 ≤ 1 at week 12 visit. These results support the effectiveness of ThermoJIS in assessing joint inflammation, as well as ThermoDAI and ThermoDAI-CRP in evaluating disease activity in RA patients.

Infrared thermography (IRT) is a non-contact, non-ionising imaging modality, providing a visual representation of temperature distribution across a surface.

We conducted a systematic search of indexed and grey literature for studies investigating IRT applications involving patients in acute care settings. Studies were categorised and described along themes identified iteratively using narrative synthesis. Quality appraisal of included studies was performed using the Quality Assessment tool for Diagnostic Accuracy Studies.

Of 1,060 unique records, 30 studies were included. These were conducted in emergency departments and intensive care units involving adult, paediatric and neonatal patients. IRT was studied for the diagnosis, monitoring or risk stratification of a wide range of individual conditions. IRT was predominantly used to display thermal change associated with localised inflammation or microcirculatory dysfunction. Existing research is largely at an early developmental stage.

We recommend that high quality diagnostic validation studies are now required for some clinical applications. IRT has the potential to be a valuable tool in the acute care setting and represents an important area for future research particularly when combined with advances in machine learning technology.

CRD 42022327619 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=327619).

Cancer is characterized by increased metabolic activity and vascularity, leading to temperature changes in cancerous tissues compared to normal cells. This study focused on patients with abnormal mammogram findings or a clinical suspicion of breast cancer, exclusively those confirmed by biopsy. Utilizing an ultra-high sensitivity thermal camera and prone patient positioning, we measured surface temperatures integrated with an inverse modeling technique based on heat transfer principles to predict malignant breast lesions. Involving 25 breast tumors, our technique accurately predicted all tumors, with maximum errors below 5 mm in size and less than 1 cm in tumor location. Predictive efficacy was unaffected by tumor size, location, or breast density, with no aberrant predictions in the contralateral normal breast. Infrared temperature profiles and inverse modeling using both techniques successfully predicted breast cancer, highlighting its potential in breast cancer screening.

Joint hypermobility syndromes, particularly chronic pain associated with this condition, including Hypermobile Ehlers-Danlos Syndrome (hEDS) and Hypermobility Spectrum Disorders (HSD), present diagnostic challenges due to their multifactorial origins and remain poorly understood from biomechanical and genomic-molecular perspectives. Recent diagnostic guidelines have differentiated hEDS, HSD, and benign joint hypermobility, providing a more objective diagnostic framework. However, incorrect diagnoses and underdiagnoses persist, leading to prolonged journeys for affected individuals. Musculoskeletal manifestations, chronic pain, dysautonomia, and gastrointestinal symptoms illustrate the multifactorial impact of these conditions, affecting both the physical and emotional well-being of affected individuals. Infrared thermography (IRT) emerges as a promising tool for joint assessment, especially in detecting inflammatory processes. Thermal distribution patterns offer valuable insights into joint dysfunctions, although the direct correlation between pain and inflammation remains challenging. The prevalence of neuropathies among hypermobile individuals accentuates the discordance between pain perception and thermographic findings, further complicating diagnosis and management. Despite its potential, the clinical integration of IRT faces challenges, with conflicting evidence hindering its adoption. However, studies demonstrate objective temperature disparities between healthy and diseased joints, especially under dynamic thermography, suggesting its potential utility in clinical practice. Future research focused on refining diagnostic criteria and elucidating the underlying mechanisms of hypermobility syndromes will be essential to improve diagnostic accuracy and enhance patient care in this complex and multidimensional context.

This study used infrared thermography (IRT) for mapping the facial and ocular temperatures of howler monkeys, to determine parameters for the diagnosis of febrile processes. There are no published IRT study in this species.

Were evaluated images of a group of monkeys kept under human care at Sorocaba Zoo (São Paulo, Brazil). The images were recorded during 1 year, in all seasons. Face and eye temperatures were evaluated.

There are statistically significant differences in face and eye temperatures. Mean values and standard deviations for facial and ocular temperature were respectively: 33.0°C (2.1) and 36.5°C (1.9) in the summer; 31.5°C (4.5) and 35.3°C (3.6) in the autumn; 30.0°C (4.3) and 35.6°C (3.9) in the winter; 30.8°C (2.9) and 35.5°C (2.1) in the spring.

The IRT was effective to establish a parameter for facial and ocular temperatures of black-and-gold howler monkeys kept under human care.

The tip of a piece of plastic fiber was dyed with thymol blue to form a temperature probe. The fiber optic sensor was calibrated on a heatboard by comparison with a K-type thermal couple. Fluorescence characteristics including fluorescence intensity, emission bandwidth, peak & barycenter wavelengths, and self-referenced intensity ratio were used to carry the information of environment temperature. Accordingly, more than five temperature sensing functions were retrieved from the fluorescent sensor. Among such functions, the emission band barycenter showed premium precision. Temperature-driven shift of the emission band barycenter has a sensitivity of 0.095 nm/K, with a nonlinearity of 2.2%FS, resolution of 4 K and repeatability of 1.8%FS. The sensor can find its applications in wearable devices and radiofrequency ablation. Finally in a verification experiment, the sensor was used to monitor the temperature of a microwave oven chamber in real time.

Low back pain affects over 20% of individuals during their lifetime, and in some patients, it may be associated with scar tissue formation after surgery. Small-fiber neuropathy and scar tissue dysfunction can lead to localized pain by affecting signals to the thalamus. Transcutaneous neuromodulation using Tape with Magnetic Particles shows promise in relieving perceived pain, modulating vascularization and the autonomic nervous system, and reducing dermal temperature. In the present case, a 24-year-old woman with L5-S1 disk herniation experienced low back pain and leg pressure. The surgical intervention provided temporary relief, but scar restrictions caused pain recurrence. Tape with Magnetic Particles application initially induced scar hypothermia and pressure tolerance during posteroanterior tests on lumbar spinous processes increased, reducing pain perception for at least 12 h. Transcutaneous neuromodulation with Tape with Magnetic Particles modulated dermal temperature immediately and for 12 h, reducing perceived pain and sustaining improvement thereafter. This highlights the potential of Tape with Magnetic Particles in managing chronic low back pain associated with scar tissue.

This study aimed to investigate the effect of human adipose tissue derived stromal vascular fraction (AD-SVF) and mesenchymal stem cells (AD-MSCs) on blood flow recovery and neovascularisation in a rat hindlimb ischaemia model.

SVF was isolated using an automated centrifugal system, and AD-MSCs were obtained from adherent cultures of SVF cells. Rats were divided into four groups of six rats each: non-ischaemia (Group 1); saline treated ischaemia (Group 2); SVF treated ischaemia (Group 3); and AD-MSC treated ischaemia (Group 4). Unilateral hindlimb ischaemia was induced in Sprague-Dawley rats via femoral artery ligation. Saline, SVF, or AD-MSCs were injected intramuscularly into the adductor muscle intra-operatively. Cell viability was calculated as the percentage of live cells relative to total cell number. Blood flow improvement, muscle fibre injury, and angiogenic properties were validated using thermal imaging and histological assessment.

The viabilities of SVF and AD-MSCs were 83.3% and 96.7%, respectively. Group 1 exhibited no significant temperature difference between hindlimbs, indicating a lack of blood flow changes. The temperature gradient gradually decreased in SVF and AD-MSC treated rats compared with saline treated rats. In addition, only normal muscle fibres with peripherally located nuclei were observed in Group 1. Groups 3 and 4 exhibited significantly fewer centrally located nuclei, indicating less muscle damage compared with Group 2. Regarding angiogenic properties, CD31 staining of endothelial cells showed similar patterns among all groups, whereas expression of vascular endothelial growth factor, as a crucial angiogenesis factor, was enhanced in the SVF and AD-MSC treated groups.

SVF and AD-MSCs improved blood flow and neovascularisation in a rat hindlimb ischaemia model, suggesting their potential ability to promote angiogenesis. Further extensive research is warranted to explore their potential applications in the treatment of severe lower extremity arterial disease.

Optical sensors with in-cell logic and memory capabilities offer new horizons in realizing machine vision beyond von Neumann architectures and have been attempted with two-dimensional materials, memristive oxides, phase-changing materials etc. Noting the unparalleled performance of superconductors with both quantum-limited optical sensitivities and ultra-wide spectrum coverage, here we report a superconducting memlogic long-wave infrared sensor based on the bistability in hysteretic superconductor-normal phase transition. Driven cooperatively by electrical and optical pulses, the device offers deterministic in-sensor switching between resistive and superconducting (hence dissipationless) states with persistence > 105 s. This results in a resilient reconfigurable memlogic system applicable for, e.g., encrypted communications. Besides, a high infrared sensitivity at 12.2 μm is achieved through its in-situ metamaterial perfect absorber design. Our work opens the avenue to realize all-in-one superconducting memlogic sensors, surpassing biological retina capabilities in both sensitivity and wavelength, and presents a groundbreaking opportunity to integrate visional perception capabilities into superconductor-based intelligent quantum machines.

XRD diffraction and IR absorption were investigated for raw loess powder and heat-treated loess powder. Raw loess retains its useful minerals, but loses their beneficial properties when calcined at 850 °C and 1050 °C. To utilize the useful minerals, loess balls were made using a low-temperature wet-drying method. The radiant energy and transmittance were measured for the loess balls. Far-infrared ray (FIR) emitted from loess bio-balls is selectively absorbed as higher vibrational energy by water molecules. FIR can raise the body's core temperature, thereby improving blood flow through the body's thermoregulatory mechanism. In an exploratory study with 40 participants, when the set temperature of the loess ball mat was increased from 25 °C to 50 °C, blood flow increased by 39.01%, from 37.48 mL/min to 52.11 mL/min, in the left middle finger; in addition, it increased by 39.62%, from 37.15 mL/min to 51.87 mL/min, in the right middle finger. The FIR emitted from loess balls can be widely applied, in various forms, to diseases related to blood flow, such as cold hands and feet, diabetic foot, muscle pain, and menstrual pain.

Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the need for interpretability in MLMI arise? What goals does one actually seek to address when interpretability is needed? To answer these questions, we identify a need to formalize the goals and elements of interpretability in MLMI. By reasoning about real-world tasks and goals common in both medical image analysis and its intersection with machine learning, we identify five core elements of interpretability: localization, visual recognizability, physical attribution, model transparency, and actionability. From this, we arrive at a framework for interpretability in MLMI, which serves as a step-by-step guide to approaching interpretability in this context. Overall, this paper formalizes interpretability needs in the context of medical imaging, and our applied perspective clarifies concrete MLMI-specific goals and considerations in order to guide method design and improve real-world usage. Our goal is to provide practical and didactic information for model designers and practitioners, inspire developers of models in the medical imaging field to reason more deeply about what interpretability is achieving, and suggest future directions of interpretability research.

To analyze whether the application of topical formulas as cosmetics or sunscreens could affect the skin thermographic readings in terms of infection control in pandemic situations.

The temperature of the skin of the dorsal region of the back and the face of 20 volunteers was followed after the application of 6 different types of gels, sunscreens, and make-up under controlled temperature and humidity conditions. High-resolution thermographic images were analyzed to calculate the temperature of treated skin compared to skin free of topical products.

The application of hydroalcoholic gel resulted in a mean drop of more than 2°C just after 1 minute followed by organic sunscreens until 1.7°C. Recovery was observed progressively until minute 9. Color make-up type formulas, rich in iron oxide as well as sunscreens with mineral filters had little or no effect on the skin thermal response.

It is possible to alter the skin temperature almost immediately by using hydroalcoholic gels and sunscreen cosmetics. So, it is possible to produce false negative data in the readings of patients screened thermically.

In this study, videothermometry's application in detecting mammary tumors in dogs is explored in-depth. The research hypothesizes that this technique can effectively identify cancerous tissues during surgery by analyzing thermal patterns. The methodology involved comparing thermal imaging results from dogs with palpable mammary nodules against a control group, focusing on capturing real-time thermal patterns. Results were significant, showing distinct thermal patterns in carcinomas. This indicates videothermometry's capability in accurately identifying micro metastases and differentiating between neoplastic and non-neoplastic changes. The study concludes that videothermometry has considerable potential in enhancing surgical precision, especially in tumor resection and safety margin definition, but emphasizes the need for further research to thoroughly understand the thermal signatures of various mammary tumors in dogs.