Application of Infrared to Biomedical Sciences

Thermography or infrared imaging is determined by detailed investigation of skin and cells’ temperatures. It helps clinicians to detect the regions of irregular chemical and blood vessel action in body tissue. The drive of biomedical industry with consequent rapid development in other areas of biomedical imaging has also strongly influenced the destiny of thermography in biomedical practice. During past few decades, the joint efforts of biomedical engineering and medical professionals have resulted in evolution of technological progress in infrared sensor technology, image processing, organized repository of knowledge, and their overall integration into a system. All these enabled the new tools of research and use in medical thermography. Thermography is a simple, noninvasive and reproducible test that can accurately reflect the inflammatory activities, and can be used safely and repeatedly, during biological course of inflammatory bowel disease. Objective of this study is presenting the possibility of infrared imaging in assessing digestive disorders such as irritable bowel syndrome, diverticulitis and Crohn’s disease.

Pain has been a problem to be differentially diagnosed for years since it has been diagnosed subjectively. Thermography can provide data of pain quantitatively as it reports detail and deep thermal variations. Hence, this method can be useful to diagnose pain objectively. It is a noninvasive complementary diagnostic approach that allows the practitioners to see and quantify alterations on skin temperature. Since in a healthy human individual, there is a high degree thermal symmetry in terms of both magnitude and pattern in the same regions in contralateral parts of the body, subtle skin temperature changes can be easily detected. According to thermography pain is classified based on which part of the body is involved. It is mostly classified in diseases as neural, inflammatory, musculoskeletal, and vascular. Nowadays with the new generation of infrared cameras and very advanced sensitive sensors, thermography has been applied in many medical applications. Pain diagnosis is one of the many uses of thermography in medicine. This chapter introduces pain and application of thermography for diagnosis of different pain categories as well as monitoring the treatments.

Nowadays, there is a considerable appreciation of thermal physiology and the connection between superficial hotness and blood perfusion. Moreover, the advantages of computer-aided digital imaging and the examination modality have considerably enhanced the trustworthiness of this technique in medical fields. The advantage of this new possibility and its applicability to medical determination of peripheral perfusion and liveliness of cells are shown by studies in diabetology. Researches demonstrate that routine checking up on foot temperature could terminate the occurrence of impairment conditions including foot ulcers and lower limb amputations. Thermography is identified as one of the popular techniques in practice today. It has potential for temperature checking up on the feet and it can be employed as an adjunctive method for modern foot examinations in diabetes.

Thermography or infrared (IR) imaging is based on a detailed investigation of skin and tissue temperatures. Its examination scheme allocates specialists to determine the regions of irregular action of carrying blood through the tissues such as angiogenesis in the body. Infrared imaging is totally safe and uses no radiation that engages the technology of the infrared camera and advanced softwares. Nowadays this technique is getting popular on medical fields because of accessible ultra-sensitive infrared cameras, advanced image processing techniques, approved protocols for interpretation of thermograms, and matured sensing devices. In more than 30 years of investigation, 800 peer-reviewed researches including more than 300,000 women contributors have exhibited thermography’s potential for diagnosing breast cancer in very early stages. Identifying relationships between neo-angiogenesis, chemical mediators, and the neoplastic developments are the aim of current studies to investigate thermal features of breast anatomy.

Comparison of breast temperature in the contralateral breast is very helpful in breast cancer diagnosis. Asymmetrical thermal diffusion might be a sign of early irregularity. Practically, most of the existent breast thermograms do not possess symmetric borders. Consequently, a suitable registration is required for comparing temperature distribution of two breasts by investigating in contrast the extracted features. In this book chapter, the proposed registration algorithm includes two steps. First, shape context, the technique as introduced by Belongie et al, was used to register two breast borders. Second, a mapping function of boundaries points was obtained and applied for mapping two breasts’ interior points. Results are very encouraging. Boundary registration was accomplished perfectly for 28 out of the 32 cases.

Color segmentation of breast thermograms can have a crucial performance in tumor detection. There is a relation between blood vessel activity and the surrounding area temperature. Once a cancer increases blood vessel activity, the cancer cells and their surrounding tissue become hotter than normal tissue. Pre-cancer and cancer cells need plenty of nutrients to multiply and survive consequently; they are highly metabolic tissue and have different thermal patterns compared to the normal one. In this paper, a comparison work is presented for three modeled color segmentation approaches: K-means, mean shift (MS), and fuzzy c-means (FCM) applied to infrared breast images. There are some drawbacks for K-means and MS approaches. Almost empty clusters may be obtained in the segmentation results using K-means algorithm. In addition, we frequently confront almost empty clusters with MS algorithm due to its sensitiveness to the window size parameter. Choosing an appropriate window size parameter is not an easy task. On the other hand, the fuzzy inherent breast thermal images aid the FCM technique to obtain more precise outcomes. Malignant tumors show hotter thermal patterns than healthy tissues and even with benign tissues. Segmenting different parts of two breasts in terms of their temperature has potential helping to identify abnormal breast tissues.

Since the introduction of breast thermography into medicine, researchers have been interested in enhancing the thermal contrast in thermograms taken at steady state. It was found that cooling the surface of the skin during long acclimation periods produced better thermal contrast, although it was agreed that acclimation periods of up to 15 min may suffice to reflect functionalities of inner skin tissues. However, the use of artificial sources for cooling the skin has revealed new functional information that complements steady state thermography findings. The method has been referred to as ‘Dynamic thermography’ and is based on monitoring skin’s thermal state after cold stress. Although dynamic thermography showed some promises in breast cancer diagnosis during the 70s, it has not received much interest till the advent of computer image processing techniques. Analytical tools such as sequential thermography, subtraction thermography, μ-thermography and thermal parametric images have been used in order to increase the accuracy of breast thermography. Other processing techniques used thermal transients of control points on the breasts to examine the change in blood perfusion induced by the presence of a breast disease. Autonomic cold challenge has also been used to identify a tumour’s blood vessels. Recent numerical methods have investigated the effectiveness of dynamic breast thermography and revealed new parameters that are strongly correlated with tumour’s depth. Here we review the state of the art in dynamic thermography as it is applied to breast diagnosis and identify some of the potential information that could be provided about breast diseases.

Breast cancer is the most common form of cancer among women globally. Detecting a tumor at its early stages is very crucial for a higher possibility of successful treatment. Cancerous cells have high metabolic rate which generate more heat compared to healthy tissue and will be transferred to the skin surface. Thermography technique has distinguished itself as an adjunctive imaging modality to the current gold standard mammography approach due to its capability in measuring the heat radiated from the skin surface for early detection of breast cancer. It provides an additional set of functional information, describing the physiological changes of the underlying thermal and vascular properties of the tissues. However, the thermography technique is shown to be highly dependent on the trained analyst for image interpretation and most of the analyses were conducted qualitatively. Therefore, the current ability of this technique is still limited especially for massive screening activity. This chapter presented a proposed technical framework for automatic segmentation and classification of abnormality on multiple in vivo thermography-based images. A new two-tier automatic segmentation algorithm was developed using a series of thermography screening conducted on both pathological and healthy Sprague-Dawley rats. Features extracted show that the mean values for temperature standard deviation and pixel intensity of the abnormal thermal images are distinctively higher when compared to normal thermal images. For classification, Artificial Neural Network system was developed and produced a validation accuracy performance of 92.5% for thermal image abnormality detection. In conclusion, this study has successfully demonstrated that for massive or routine screening activities, the proposed technical framework could provide a highly reliable clinical decision support to the clinicians in making a diagnosis based on the medical thermal images.

Breast cancer is considered to be one of the major causes for high mortality rates in young women in the developing countries. Survival rate in breast cancer patients may be improved significantly by early detection. In order to detect cancer in its initial stages breast screening is recommended for women over 40 years of age. Due to the limitations of existing breast cancer screening techniques alternative modalities such as thermography are being explored. An elevation in local surface temperature due to an underlying pathology is considered as one of the earliest indications of an underlying cancer. Such regions are represented as hotspots on a conventional thermogram. Detection of these hotspots from conventional breast thermograms is quite challenging, mainly due to incomplete image acquisition. A novel technique called rotational thermography has been developed to address this issue. In this chapter, a frame work has been presented for developing a breast cancer screening system using thermograms acquired with this new imaging modality. Image features are extracted from rotational thermograms in spatial, bispectral, and multi-resolution domains. Optimal features are identified using genetic algorithm and automatic classification is performed using support vector machine. In addition to screening, attempt has been made to characterize a detected abnormality as benign or malignant. As rotational thermography acquires images of the breast in multiple views, study is carried out to locate the position of the tumor in correlation with ultrasound and biopsy findings. Thus the potential of the system for screening, characterization, and localization of breast abnormalities is explored.

This chapter presents some developments and researches on using breast infrared images in Brazil (Visual Lab group of the Federal Fluminense University). These researches focus on comparing protocols for data acquisition using a FLIR SC 620 infrared (IR) camera; preprocessing the acquired data (using operations such as region of interest or ROI extraction, image registration and some other operations to prepare the images or thermal matrices to be used in computations); 3D reconstruction and, diagnostic recommendations from the IR data. These are steps for development of computer tools for screening breast diseases, mainly, to be used on public health system (named in Brazil: “Sistema Único de Saúde”—SUS). After experimentations and comparisons among the diversity of recommendations and ways of data acquisition reported in the literature, we propose a new protocol to IR data capture and storage. With these, we developed a web site that can be used by all researchers interested in development of works in such subject. The site has public access and presents several ground truths of intermediated developments of the research as segmentation of the ROI, sets of features to be used for comparing artificial intelligence methods for decision making, and some techniques for ROI registration. Our intension is to provide materials to those interested in infrared researches for breast disease. For the development of IR applications are very important compare outcomes in disease detection (and diagnosis) and to use different strategies for features extraction, decision-making, and dimensionality reduction. However, in order to promote fair conditions for comparisons, we have to begin in a more standardized way to go further and for this we invite all interest in the same theme to use a unified procedure for data acquisition.

In the present work coupled stationary bioheat transfer equations are considered. The cancerous breast is characterized by two areas of dissimilar thermal properties: the glandular and tumor tissues. The tumorous region is modeled as a two-phase composite where parallel periodic isotropic circular fibers are embedded in the glandular isotropic matrix. The periodic cell is assumed square. The local problem on the periodic cell and the homogenized equation are stated and solved. The temperature distribution of the cancerous breast is found through a numerical computation. A mathematical and computational model is integrated by FreeFem++.

Dynamic Angiothermography (DATG) is a noninvasive technique for the diagnosis of breast cancer. The instrument consists of a thin plate with liquid crystals that changes color due to a change in temperature, consequently offering an image of breast vasculature. DATG is based on the angiogenesis theory on tumor initiation, development, and growth. A tumor needs new vessels. Therefore, by studying the changes in the pattern of vascular blood supply, it is also possible to diagnose neoplasms very early. In particular, it is shown that every human being has his or her own vascular pattern which, in the absence of disease, does not vary throughout the life time. By repeating DATG periodically, an efficient control of the onset of disease is possible, even in its early stages. This is not new but still little-known technique which is a component of the overall diagnostic techniques for the study and prevention of breast cancer that serves to offer a complete clinical picture of the patient. The great advantages of DATG are: it does not use radiation; it is not invasive or painful; it is low-cost and can be repeated periodically and successfully with no drawbacks. The angiothermographic examination thus makes it possible to visualize the breast vascularity pattern without using contrast medium. On the other hand, while highlighting changes in mammary vascularization, DATG is not able to indicate the size or depth of the tumor; even if recent researches (based on the approximated solution of the inverse Fourier heat equation) show the possibility to evaluate the depth of the tumor. This paper, after the introduction in Sect. 1, starts with a description of historical context in Sect. 2, and outlines the instrumentation in Sect. 3. Section 4 describes the technique, while a comparison with other diagnostic techniques is provided in Sect. 5. To close, Sect. 6 offers a practical guide on the use of this method.

Body temperature is a significant indicator of illness and hence is a useful parameter for clinical diagnosis. Among various techniques available for accurate and reliable measurement of subject temperature, infrared thermography is a relatively new methodology. However, it has become popular because of its noncontact, noninvasive, and real-time temperature measurement capability. During the last few decades, numerous applications of infrared thermography are reported in the field of medical sciences, which are rapidly growing. Diabetes is a metabolic disorder associated with high blood sugar levels over prolonged duration. One in every 11 adult population of the world is affected by diabetes and for every 6 s, one person dies from diabetes-induced complications. Therefore, a worldwide dedicated effort to prevent diabetic complications by early detection is important. Studies so far reveal that infrared thermography is capable of detecting subtle changes in skin temperature distribution in diabetic-at-risk foot and is capable of early detection diabetic-related peripheral neuropathy and vascular disorders. This chapter attempts to highlight the applications of infrared thermography in the early detection of diabetic neuropathy and vascular disorder. The basics of infrared thermography, classification of medical thermography techniques, details of infrared camera, ideal experimental conditions, data analysis, etc. along with typical case studies are discussed in detail.

Peripheral arterial disease (PAD) is an atherosclerotic condition that can result in reduced lower limb tissue perfusion. It is associated with significant comorbidity including coronary artery disease (CAD) and cerebrovascular disease. One of the most currently utilised diagnostic tools is the ankle brachial pressure index, which is time consuming, requires significant user training and is unreliable in diabetics due to vessel calcification leading to falsely elevated results. The aim of this pilot study was to explore the potential use of thermal imaging in identifying PAD. In 44 patients (24 male; mean (SD) age 67 [12] years) thermal images of three regions of interest (ROI’s) on the feet were collected within a normothermic measurement room. The ROI’s for each foot included the first toe (T), proximal foot (PF) and whole foot (WF). The ankle brachial pressure index (ABPI) reference test was collected to make a diagnosis of PAD (ABPI < 0.9). Parametric statistics were employed and a p value <0.05 considered statistically significant. Twenty-three patients had significant PAD in at least one leg (Mean ABPI 0.64; Range 0.32–0.86) while 26 patients had a normal ABPI (non-PAD) in at least one leg (Mean ABPI 1.14; Range 0.9–1.46). There were no significant ROI differences between PAD (Mean WF temperature 30.3 °C; SD 0.8) and non-PAD feet (Mean WF temperature 31.0 °C; SD 0.7) for their mean or SD values. The temperature gradient (toe-proximal foot) was close to −1 °C but this was not significantly different between the groups. Furthermore, right minus left whole foot temperature differences were not significant. Absolute, gradient, spatial and bilateral skin temperature differences of the feet have been quantified in PAD and non-PAD legs and have found no significant differences overall. This pilot study indicates that thermal imaging from resting measurements is unlikely to be of diagnostic value in detecting significant PAD. Furthermore, the study also raises questions about the apparent misconception that in PAD the foot temperatures are usually significantly reduced.

Thirty participants with healthy feet were imaged in the same way on two separate occasions (an average of 4 weeks apart). Overall, feet were found to be thermally symmetric although absolute temperature could vary considerably between visits. Temperature differences at specific sites on the foot sometimes exceeded the threshold of 2.2 °C regarded as clinically significant when looking for evidence of inflammation prior to skin breakdown in diabetes. At least one site exceeded this threshold in nine (30%) participants (the same figure for both visits). However, when looking for significant thermal asymmetry it is important to rule out transient changes by repeated imaging and to refer to baseline images.

We developed a method for diagnosing fetal cerebral hypoxia with a thermal imaging camera. The method is based on the following detected principle: hypoxia and ischemia reduce the intensity of thermal radiation from tissues. Infrared thermography was performed in 35 pregnant women with a ThermoTracer TH9100XX thermal imaging camera (NEC, USA) in the temperature range of 26–36 °C. The research results showed that the local temperature of the skin in the parietal head part in live fetuses during delivery and immediately after birth ranged from 31.6 to 36.1 °C. It is found that normally an area of local hyperthermia might be observed on the top of the fetal head, and the temperature in this area might be 0.5–4.0 °C more than the temperature of the areas close to it. This area is located above the central suture of the skull, and has oblong shape. Monitoring the dynamics of temperature in the central suture allows us to evaluate the oxygen supply to fetal brain cortex during delivery. In this context, if the temperature drop areas are not observed in fetal head skin during his passing through the birth canals, it indicates the possibility of giving birth to a healthy child. In its turn, the occurrence of local hypothermia over the central suture of the skull indicates the hypoxic and ischemic damage to the fetal brain cortex and requires immediate hyper-oxygenation of the fetus blood. To increase the oxygen delivery to the fetus, we suggested giving the mother oxygen through a face mask and instruct her to breathe it in until “feeling drunk”. We also suggest putting oxygen face mask on the fetus inside the mother’s womb for artificial intrauterine ventilation of fetus lungs with breathing gas. In addition, in order to prevent fetal brain cortex cells from dying from hypoxia we suggested cooling the fetal head as soon as it comes out of the birth canal. We also propose to document the child health status in the final stage of childbirth by recording the dynamics of local temperature in the head skin area over the gap between the parietal skull bones with infrared thermography.

This is an overview of active thermal imaging methods in medical diagnostics using external thermal stimulation. In this chapter, several clinical cases diagnosed using the active dynamic thermography method, ADT, are presented. Features of this technology are discussed and main advantages underlined. Applications in skin burn diagnostics and quantitative evaluation leading to modern classification of burned patients for further treatment are shown. Also the use of thermal imaging in cardiosurgery is discussed. A method of quantitative evaluation of the healing progress of post-cardiosurgery wounds is presented. The ADT method gives quantitative description of thermal structural data, supplementing well-established static thermal imaging that carry functional physiological information. Combination of both modalities supports the idea of modern multimodality approach in medical diagnostics.

Respiratory rate is very important vital sign that should be measured and documented in many medical situations. The remote measurement of respiration rate can be especially valuable for medical screening purposes (e.g. severe acute respiratory syndrome (SARS), pandemic influenza, etc.). In this chapter we present a review of many different studies focused on the measurements and estimation of respiration rate using thermal imaging methods. Additionally, we present results of our research focused on the evaluation of different respiration rate estimators for the needs of data processing of image sequences recorded by small, mobile thermal cameras. We used small thermal camera modules in the prototypes of smart glasses for the evaluation of different parameters related to respiration activities. The chapter presents the used methodology and results of the respiration rate analysis, detection of apnea events, description of respiration patterns and other parameters that can be analyzed for respiration waveforms derived from the regions of the nostrils or mouth in thermal video sequences.

Infrared thermography (IRT), one of the most valuable tools, is used for noncontact, noninvasive, and rapid monitoring of body temperature; this has been used for mass screening of febrile travelers at places such as airport quarantine stations for over 10 years after the 2003 severe acute respiratory syndrome (SARS) outbreak. The usefulness of thermography for mass screening has been evaluated in many recent studies; its sensitivity varies from 40 to 89.4% under various circumstances. In this chapter, we perform IRT evaluations for detecting febrile international travelers entering Japan at Nagoya Airport, immediately after the SARS epidemic, from June 2003 to February 2004, and at Naha International Airport from April 2005 to March 2009. The correlation of body surface temperature measured via thermography with the axillary temperature was significant. Through IRT, febrile individuals were detected with good accuracy and the detection accuracy was improved by corroborating surveillance with self-reporting questionnaires. However, there are several limitations associated with the use of IRT for fever screening. For instance, taking antifebrile medications results in rapid modification of the body temperature and directly affects the efficiency of IRT. To solve this unreliability and obtain higher accuracy in mass screening, we have developed a novel infection screening system using multisensor data, i.e., heart and respiration rates are determined by microwave radar in noncontact manner and facial skin temperature is monitored through IRT. The detection accuracy of the system improved, which is notably higher compared to the conventional screening method using only IRT.

Tear film instability is a major cause of dry eye (DE) disease. The lack of stability of the tear film may be associated with optical aberrations, visual disturbances, and ocular surface damage. It is clinically important to detect tear instability in DE as the treatment may involve specific measures such as chronic eyelid warming therapy. To achieve this, a practical and rapid method to analyze the relevant features from different regions of the ocular surface in DE will be useful. Thus, in this chapter, efficiency of using the upper half and lower half regions of the ocular surface (cornea + conjunctiva) in the detection of evaporative dry eye is assessed using infrared thermography images. Here, we define the ocular surface as the exposed area of the cornea and the bulbar conjunctiva during natural blinking conditions. Infrared thermography images are acquired from each eye of normal and DE participants. Discrete wavelet transform (DWT) and Gabor transform are used to extract the salient features from the 1st, 5th, and 10th frames of the infrared thermography images after the first blink is subjected to segmentation to obtain the upper half and lower half ocular regions. Each segmented region is decomposed up to three levels using DWT and Gabor transform is performed on the DWT coefficients. Principal component analysis (PCA) is performed on these extracted features to reduce the number of features, and PCA coefficients are ranked using t-value and fed to support vector machine (SVM) classifier. Using the 1st, 5th, and 10th frames of the upper half of ocular region after the first blink, we achieved classification accuracies of (i) 82.3, 89.2, 88.2% for the left eye and (ii) 93.4, 81.5, 84.4% for the right eye, respectively. Similarly, using 1st, 5th, and 10th frames of lower half of ocular regions we achieved accuracies of (i) 95.0, 95.0, 89.2% and (ii) 91.2, 97.0, 92.2% for the left and right eyes, respectively. This study shows that the lower half of the eye is superior to the upper half for the purpose of DE detection using our technique. The proposed algorithm is efficient, simple, and may be employed in polyclinics or hospitals for faster DE assessment.

Measurement of body temperature is one of the cornerstones of clinical assessment in medicine. Skin, the largest organ of the human body, is essentially a temperature mosaic determined by the rate of blood flow through arterioles and capillaries adjacent to the skin. This makes the conventional methods of ‘spot’ measurement rather limited in providing detailed information of regional skin temperature. Infrared (IR) thermal imaging however has the potential to provide a robust method of surface temperature mapping in disease states where pathology disturbs the ‘normal’ distribution of blood flow to skin. To advance image interpretation from the conventional qualitative narrative to a quantitative and robust system, analytical developments focus on digital images and require computer-aided systems to produce results rapidly and safely. Hierarchical clustering-based segmentation (HCS) provides a generic solution to the complex interpretation of thermal data (pixel by pixel) to produce clusters and boundary regions at levels not discernible by human visual processing. In this chapter, HCS has been used to aid the interpretation of wound images and to identify variations in temperature clusters around and along the surgical wound for their clinical relevance in wound infection.

Thermal tomography is a new tool in medical diagnosis. It is based on so-called cold provocation. It is practically realized be a weak cooling of an upper layer of the skin. As it is noninvasive and harmless it can be applied as a screening procedure and repeated frequently. Using thermographic camera, the temperature recovery of the skin in time is measured and analyzed. In this chapter, three new methods of thermal tomography are presented. First, one is based on the analysis in time domain. The temperature versus time is approximated by the function which is a combination of exponential and error functions. The chosen parameters of this approximation that can be interpreted as the time constants are used then to visualize the blood vessels. The second approach uses the thermal modeling of the multilayer skin structure. The inverse thermal problem in frequency domain is solved to estimate the thermal parameters of each layer of the skin, including perfusion. The last procedure uses the wavelet transform (WT) to convert the large sequence of thermal images and reduce it just one amplitude and one phase image for an appropriate scale. The new two-step algorithm of WT for the image sequence is presented. This approach speeds up the analysis significantly.

Transpiration from porous materials such as leaves, stones, or human skin plays an important role in thermographic analysis due to evaporation. The change of physical state from liquid to vapor takes place at the interface of materials with surrounding air exactly where thermal infrared radiation is radiated. This chapter studies with the possibility to obtain quantitative evaluation of evaporation rate from non contact temperature measurements. The use of the localized high-intensity cooling on surface caused by evotranspiration has to be considered as a tool of inspection in diagnostics. A wide review of applications in plant physiology is here presented and some cases of follow-up of trauma in athletes are as well reported.

A possibility of fast, safe, and efficient imaging of superficial veins with a thermal imager is demonstrated in experiments with pigs, in studies with healthy adult volunteers, and in clinical observations of adult patients when providing vital medical care in emergency situations. The research describes the original techniques for infrared veins imaging enabling the authors to lay the basis for infrared venography. In order to image superficial veins, we suggest infrared monitoring of local temperature dynamics in the selected part of the body surface under the conditions of artificial multidirectional changes in temperature of veins and/or surrounding tissues. The chapter describes techniques for infrared imaging of the superficial veins in limbs and breast, and provides infrared thermograms of a hand, a forearm, a shoulder, a foot, and a breast, thus showing the prospects of superficial veins imaging using infrared phlebography and temperature-based “displaying.” It explains the essence of temperature-based veins “displaying,” developed by authors and called “temperature contrasting.” It describes the techniques for artificial changes in local venous temperature by changing the temperature of venous blood and/or artificial plasma extender, or by artificial cooling of the tissues surrounding the vein. It also shows the advantages of infrared phlebography over other radiology methods to address urgent and repeated imaging of superficial veins in critical situations to optimize intravascular access for sampling venous blood, its subsequent laboratory testing, and intravenous injections of medications.

The Microvascular Diagnostics Service at Freeman Hospital, Newcastle upon Tyne, holds a comprehensive range of optical and thermal technologies utilised to study the microcirculation both for clinical and research purposes. In the recent years, collaboration has been formed with the colorectal surgical service to look at the feasibility and clinical value of intraoperatively assessing bowel perfusion using microvascular imaging technologies. Anastomotic failure is the most serious complication following colorectal resection that can lead to re-operation, permanent stoma, and even death. The current practice of assessing blood perfusion at the anastomosis bowel ends by direct inspection of bowel pulsatility, bleeding, and tissue coloration has been demonstrated to lack predictive accuracy. The medical community is striving to improve the outcome of colorectal resections and a key aspect in achieving this goal will be the development of more objective techniques to intraoperatively assess and quantify the bowel perfusion. We believe that microvascular imaging technology could play a key role in this respect. In this chapter, we describe two case studies which show the feasibility of performing thermal and laser speckle contrast imaging measurements intraoperatively for assessing bowel perfusion during colorectal resection surgery. This experience could pave the way to a number of other applications for these technologies in the surgical arena.

Thyroid cancer is said to be the second most common type of cancer in female individuals and the third in males by 2030, according to projections. In general, detecting cancer in its early stages improves the chance of survival of the individual. Thermography is a diagnostic tool that has been increasingly used to detect cancer and abnormalities, including that of thyroid. Various methods to segment and detect hot regions in thermograms and, consequently, to detect suspicious tissues present in these images have been proposed. It is well known that medical diagnosis yields a great deal of information. Thus, physicians have to comprehensively analyse and evaluate this information in a short period of time, which is infeasible in most cases. In this work, we perform a general review of thermography, focusing on the thyroid analysis. We propose protocols for image acquisiton and an autonomous registration for thyroid images. We also perform analyses of the image data, which include feature extraction, image processing, and a possible approach for classification of healthy or unhealthy patients. In summary, this work presents a pilot project for detection of tumors in our university hospital, which is part of an effort to support preventive medical actions in our endocrinology department. Under some future adjustments, this project will be submitted for approval by the ethics and research committee of Hospital Universitário Antonio Pedro at Universidade Federal Fluminense (HUAP-UFF) and to the Brazilian Ministry of Health Ethical committee under the name: Evaluation of the importance of thermography to aid diagnosis of thyroid nodules of patients in HUAP-UFF (in Portuguese: Avaliação da importância da termografia no auxílio à investigação diagnóstica de nódulos tireoidianos em pacientes acompanhados no HUAP-UFF).

Nowadays, thermal infrared imaging (IRI) is thought to be a fascinating and promising complementary imaging tool regarding typical gold-standard medical imaging for differential diagnosis. This chapter presents the commonly used approaches for modeling thermal infrared data for differential diagnosis purposes. Two main modeling approaches were proposed, i.e., (i) qualitative modeling approach based on using statistical and machine learning techniques, (ii) quantitative modeling approach based on performing mathematical/analytical modeling of the thermoregulatory processes by using three main approaches: (i) empirically using automatic control theory, (ii) non-empirically using bioheat equations and (iii) semi-empirically using both bioheat equations and automatic control theory. Also, three main modeling approaches based on control system theory were presented, i.e., (i-a) time domain analysis of the thermoregulatory system’s characteristics through a direct estimation of the closed loop dynamic response parameters of a prototype second-order system, (i-b) a direct identification of thermoregulatory system as a second-order system plus delay time (SOPDT) from a closed-loop step response, and (i-c) a state-space representation of the thermoregulatory system as a first-order differential equation from the experimental IR temperature curves. Moreover, this chapter summarizes the advantages and disadvantages of each modeling approach highlighting its assumptions and approximations. By implementing the proposed modeling approaches, thermal infrared imaging has been demonstrated to be able to (i) identify significant averaged and asymmetric temperature parameters that could be used for disease classification, (ii) provide a direct functional IR indicators of the thermoregulatory malfunctions/alternations indirectly assess the severity of functional perturbation of the autonomic sympathetic and parasympathetic physiological activations in the presence of a disease, (iii) compute physiological information, such as localized blood flow, cardiac pulse, and breath rate, and (iv) identify skin’s thermal parameters, location of heat source (particularly the vessels), depth of heat source used for defining the location and geometrical shape of the affected-area, mostly required for tumor detection, and (v) provide a clear description of the underlying alterations in the main thermoregulatory functions as for example, environmental heat exchange process, vasoconstriction and/or vasodilation, and sweating actions. The authors consider this chapter as a good material that provides a great insight about the utility of thermal infrared imaging for medical diagnostic purposes.

3D thermography systems that combine 3D geometric data and 2D thermography data enable users to have a more accurate representation of the surface temperature distribution and aid in its interpretation. A system for 3D dynamic infrared thermography comprising two units is presented; each unit consists of an off-the-shelf depth camera rigidly mounted to a FLIR thermal camera. The units are fixed on the arms of the device that allow their placement in desired positions near the subject. To generate a single 3D thermogram, the data obtained from the depth cameras is registered with the images from the thermal cameras. The process of generating a 3D thermogram is repeated several times while thermally stimulating the surface of the subject to produce a series of 3D thermograms. The developed system provides a number of advantages in research for biomedical applications, such as the correct temperature measurements on curved surfaces, the possibility to select regions of interest by taking into account the shape of the subject and the possibility to use the 3D data to easily eliminate the background from 2D thermograms.