scholarly journals Advances in Thermal Image Analysis for the Detection of Pregnancy in Horses Using Infrared Thermography

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 191
Author(s):  
Małgorzata Domino ◽  
Marta Borowska ◽  
Natalia Kozłowska ◽  
Łukasz Zdrojkowski ◽  
Tomasz Jasiński ◽  
...  
Keyword(s):  
Infrared Thermography ◽  
Imaging Technique ◽  
Texture Features ◽  
Digital Processing ◽  
Heat Emission ◽  
The Body ◽  
Image Texture ◽  
Thermal Images ◽  
Color Models ◽  
Matrix Algorithms

Infrared thermography (IRT) was applied as a potentially useful tool in the detection of pregnancy in equids, especially native or wildlife. IRT measures heat emission from the body surface, which increases with the progression of pregnancy as blood flow and metabolic activity in the uterine and fetal tissues increase. Conventional IRT imaging is promising; however, with specific limitations considered, this study aimed to develop novel digital processing methods for thermal images of pregnant mares to detect pregnancy earlier with higher accuracy. In the current study, 40 mares were divided into non-pregnant and pregnant groups and imaged using IRT. Thermal images were transformed into four color models (RGB, YUV, YIQ, HSB) and 10 color components were separated. From each color component, features of image texture were obtained using Histogram Statistics and Grey-Level Run-Length Matrix algorithms. The most informative color/feature combinations were selected for further investigation, and the accuracy of pregnancy detection was calculated. The image texture features in the RGB and YIQ color models reflecting increased heterogeneity of image texture seem to be applicable as potential indicators of pregnancy. Their application in IRT-based pregnancy detection in mares allows for earlier recognition of pregnant mares with higher accuracy than the conventional IRT imaging technique.

scholarly journals The Effect of Rider:Horse Bodyweight Ratio on the Superficial Body Temperature of Horse’s Thoracolumbar Region Evaluated by Advanced Thermal Image Processing

Animals ◽  
2022 ◽  
Vol 12 (2) ◽  
pp. 195
Author(s):  
Małgorzata Domino ◽  
Marta Borowska ◽  
Anna Trojakowska ◽  
Natalia Kozłowska ◽  
Łukasz Zdrojkowski ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Texture Features ◽  
Image Texture ◽  
Gray Level ◽  
Image Texture Analysis ◽  
Thermal Images ◽  
Thoracolumbar Region ◽  
Thermal Features ◽  
Occurrence Matrix ◽  
The Impact

Appropriate matching of rider–horse sizes is becoming an increasingly important issue of riding horses’ care, as the human population becomes heavier. Recently, infrared thermography (IRT) was considered to be effective in differing the effect of 10.6% and 21.3% of the rider:horse bodyweight ratio, but not 10.1% and 15.3%. As IRT images contain many pixels reflecting the complexity of the body’s surface, the pixel relations were assessed by image texture analysis using histogram statistics (HS), gray-level run-length matrix (GLRLM), and gray level co-occurrence matrix (GLCM) approaches. The study aimed to determine differences in texture features of thermal images under the impact of 10–12%, >12 ≤15%, >15 <18% rider:horse bodyweight ratios, respectively. Twelve horses were ridden by each of six riders assigned to light (L), moderate (M), and heavy (H) groups. Thermal images were taken pre- and post-standard exercise and underwent conventional and texture analysis. Texture analysis required image decomposition into red, green, and blue components. Among 372 returned features, 95 HS features, 48 GLRLM features, and 96 GLCH features differed dependent on exercise; whereas 29 HS features, 16 GLRLM features, and 30 GLCH features differed dependent on bodyweight ratio. Contrary to conventional thermal features, the texture heterogeneity measures, InvDefMom, SumEntrp, Entropy, DifVarnc, and DifEntrp, expressed consistent measurable differences when the red component was considered.

scholarly journals Pathophysiology of Fever and Application of Infrared Thermography (IRT) in the Detection of Sick Domestic Animals: Recent Advances

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2316
Author(s):  
Daniel Mota-Rojas ◽  
Dehua Wang ◽  
Cristiane Gonçalves Titto ◽  
Jocelyn Gómez-Prado ◽  
Verónica Carvajal-de la Fuente ◽  
...  
Keyword(s):  
Body Temperature ◽  
Infrared Thermography ◽  
Core Body Temperature ◽  
The Body ◽  
Farm Animals ◽  
Economic Losses ◽  
Febrile Response ◽  
Temperature Range ◽  
Stable Temperature ◽  
Core Body

Body-temperature elevations are multifactorial in origin and classified as hyperthermia as a rise in temperature due to alterations in the thermoregulation mechanism; the body loses the ability to control or regulate body temperature. In contrast, fever is a controlled state, since the body adjusts its stable temperature range to increase body temperature without losing the thermoregulation capacity. Fever refers to an acute phase response that confers a survival benefit on the body, raising core body temperature during infection or systemic inflammation processes to reduce the survival and proliferation of infectious pathogens by altering temperature, restriction of essential nutrients, and the activation of an immune reaction. However, once the infection resolves, the febrile response must be tightly regulated to avoid excessive tissue damage. During fever, neurological, endocrine, immunological, and metabolic changes occur that cause an increase in the stable temperature range, which allows the core body temperature to be considerably increased to stop the invasion of the offending agent and restrict the damage to the organism. There are different metabolic mechanisms of thermoregulation in the febrile response at the central and peripheral levels and cellular events. In response to cold or heat, the brain triggers thermoregulatory responses to coping with changes in body temperature, including autonomic effectors, such as thermogenesis, vasodilation, sweating, and behavioral mechanisms, that trigger flexible, goal-oriented actions, such as seeking heat or cold, nest building, and postural extension. Infrared thermography (IRT) has proven to be a reliable method for the early detection of pathologies affecting animal health and welfare that represent economic losses for farmers. However, the standardization of protocols for IRT use is still needed. Together with the complete understanding of the physiological and behavioral responses involved in the febrile process, it is possible to have timely solutions to serious problem situations. For this reason, the present review aims to analyze the new findings in pathophysiological mechanisms of the febrile process, the heat-loss mechanisms in an animal with fever, thermoregulation, the adverse effects of fever, and recent scientific findings related to different pathologies in farm animals through the use of IRT.

scholarly journals Research on college gymnastics teaching model based on multimedia image and image texture feature analysis

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Ying Wu ◽  
Jikun Liu
Keyword(s):  
Human Body ◽  
Rapid Development ◽  
Texture Feature ◽  
Texture Features ◽  
Dynamics Simulation ◽  
Image Texture ◽  
Whole Body ◽  
Database Modeling ◽  
Rigid Model ◽  
The Subject

AbstractWith the rapid development of gymnastics technology, novel movements are also emerging. Due to the emergence of various complicated new movements, higher requirements are put forward for college gymnastics teaching. Therefore, it is necessary to combine the multimedia simulation technology to construct the human body rigid model and combine the image texture features to display the simulation image in texture form. In the study, GeBOD morphological database modeling was used to provide the data needed for the modeling of the whole-body human body of the joint and used for dynamics simulation. Simultaneously, in order to analyze and summarize the technical essentials of the innovative action, this experiment compared and analyzed the hem stage of the cross-headstand movement of the subject and the hem stage of the 180° movement. Research shows that the method proposed in this paper has certain practical effects.

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses

2021 ◽  
pp. 016173462199809
Author(s):  
Dhurgham Al-karawi ◽  
Hisham Al-Assam ◽  
Hongbo Du ◽  
Ahmad Sayasneh ◽  
Chiara Landolfo ◽  
...  
Keyword(s):  
Gabor Filter ◽  
Empirical Evaluation ◽  
Texture Features ◽  
Image Texture ◽  
Support Vector ◽  
Simple Majority ◽  
Ultrasound Scan ◽  
Histograms Of Oriented Gradients ◽  
The Individual ◽  
Ovarian Masses

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and their extraction methods. Several texture features have been recently applied in discriminating malignant and benign ovarian masses by analysing B-mode images from ultrasound scan of the ovary with different levels of performance. However, comparative performance evaluation of these reported features using common sets of clinically approved images is lacking. This paper presents an empirical evaluation of seven commonly used texture features (histograms, moments of histogram, local binary patterns [256-bin and 59-bin], histograms of oriented gradients, fractal dimensions, and Gabor filter), using a collection of 242 ultrasound scan images of ovarian masses of various pathological characteristics. The evaluation examines not only the effectiveness of classification schemes based on the individual texture features but also the effectiveness of various combinations of these schemes using the simple majority-rule decision level fusion. Trained support vector machine classifiers on the individual texture features without any specific pre-processing, achieve levels of accuracy between 75% and 85% where the seven moments and the 256-bin LBP are at the lower end while the Gabor filter is at the upper end. Combining the classification results of the top k ( k = 3, 5, 7) best performing features further improve the overall accuracy to a level between 86% and 90%. These evaluation results demonstrate that each of the investigated image-based texture features provides informative support in distinguishing benign or malignant ovarian masses.

Thermal windows on the body surface of African elephants (Loxodonta africana) studied by infrared thermography

2010 ◽  
Vol 35 (4) ◽  
pp. 182-188 ◽  
Author(s):  
Nicole M. Weissenböck ◽  
Christoph M. Weiss ◽  
Harald M. Schwammer ◽  
Helmut Kratochvil
Keyword(s):  
Infrared Thermography ◽  
Body Surface ◽  
Loxodonta Africana ◽  
The Body ◽  
African Elephants

Investigation of Bending Fatigue of Composite Plates by Using Infrared Thermography

2011 ◽  
Vol 268-270 ◽  
pp. 406-411 ◽  
Author(s):  
Ömer Sinan Şahin ◽  
Murat Selek ◽  
Şirzat Kahramanlı
Keyword(s):  
Infrared Thermography ◽  
Heat Generation ◽  
Temperature Rise ◽  
Epoxy Composite ◽  
Composite Plates ◽  
Fatigue Loading ◽  
Thermal Camera ◽  
Thermal Images ◽  
Bending Fatigue ◽  
Damage Initiation

In this study, the temperature rise of composite plates with a hole during fatigue loading was investigated. Woven glass/epoxy composite plates with eight plies were subjected to bending fatigue loading and materials were observed by using a thermal camera during the test. Previous works showed that a heat generation can form due to internal friction and damage formation. Therefore, a thermographic infrared imaging system was used to detect the temperature rise of composite specimens. During the tests, the thermal images of the specimens have been recorded by a thermal camera and then transferred to the image processing program which has been developed by using MATLAB. By using these thermal images, the spot temperatures of the specimen were obtained by using artificial neural networks. The obtained temperatures show local increase at places where the heat generation localized. These regions considered being the probable damage initiation sites. It is shown in this study that most probable damage initiation zones in the woven glass/epoxy composite material can be detected by using infrared thermography (IRT) approach prior to failure.

Fast Intra-Frame Encoding Algorithm Based on Image Texture Features for HEVC

2017 ◽  
Vol 54 (7) ◽  
pp. 071003
Author(s):  
孙学斌 Sun Xuebin ◽  
陈晓冬 Chen Xiaodong ◽  
肖禹泽 Xiao Yuze ◽  
汪 毅 Wang Yi ◽  
郁道银 Yu Daoyin
Keyword(s):  
Texture Features ◽  
Image Texture

Evaluation of infrared technology to detect category I and suspected deep tissue injury in hospitalised patients

2019 ◽  
Vol 28 (Sup12) ◽  
pp. S9-S16
Author(s):  
Fazila Abu Bakar Aloweni ◽  
Shin Yuh Ang ◽  
Yee Yee Chang ◽  
Xin Ping Ng ◽  
Kai Yunn Teo ◽  
...  
Keyword(s):  
Skin Temperature ◽  
Infrared Thermography ◽  
Tissue Injury ◽  
Mean Difference ◽  
Deep Tissue ◽  
Thermal Images ◽  
Deep Tissue Injury ◽  
Hospitalised Patients ◽  
Significant Difference ◽  
The Mean

Objective: To evaluate the use of an infrared thermography device in assessing skin temperature among category I pressure ulcer (PU) and/or suspected deep tissue injuries (SDTI) with intact skin. Methods: An observational cross-sectional study design was used. Adult inpatients (cases) who had a category I PU or suspected deep tissue injury (skin intact) on the sacral or heel during the study period (March to April 2018) were recruited. Patients without a PU were also recruited to act as control. Thermal images of the patient's PU site and non-PU site were taken within 24 hours of PU occurrence. Thermal images of the control patients (no PU) were also taken. Each PU case was matched to three control patients in terms of age, gender, race and anatomical sites. All thermal images were taken using a portable CAT S60 Thermal Imaging Rugged Smartphone (Caterpillar Inc., US) that provided readings of the skin temperature in degrees Celsius. Results: A total of 17 cases and 51 controls were recruited. Among the cases, the mean difference in skin temperature between the PU site (mean: 31.14°C; standard deviation [SD]: 1.54) and control site within the cases (mean: 28.93°C; SD: 3.47) was significant (difference: 2.21±3.66°C; p=0·024). When comparing between all cases and controls, the mean temperature difference was non-significant. When comparing between the category I PU and suspected deep pressure injury cases, the mean difference was also non-significant. Conclusion: Using infrared thermography technology at the bedside to measure skin temperature will support the clinical diagnosis of patients with skin types I to III. However, there is a need for a more accurate and objective measurement to identify and diagnose early category I PU or suspected deep tissue injury in adult patients with darker skin types 4 and above, enabling early initiation of preventive measures in the hospital acute care setting.

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