Improving Quantitative Infrared Imaging for Medical Diagnostic Applications

Infrared (IR) thermography is a non-ionizing and non-invasive imaging modality that allows the measurement of the spatial and temporal variations of the infrared radiation emitted by the human body. The emitted radiation and the skin surface temperature that can be derived from the emitted radiation data carry a wealth of information about different processes within the human body. To advance the quantitative use of IR thermography in medical diagnostics, this dissertation investigates several issues critical to the demands imposed by clinical applications. We developed a computational thermal model of the human skin with multiple layers and a near-surface lesion to understand the thermal behavior of skin tissue in dynamic infrared imaging. With the aid of this model, various cooling methods and conditions suitable for the clinical application of dynamic IR imaging are critically evaluated. The analysis of skin cooling provides a quantitative basis for the selection and optimization of cooling conditions in the clinical practice of dynamic IR imaging. To improve the quantitative accuracy for the analysis of dynamic IR imaging, we proposed a motion tracking approach using a template-based algorithm. The motion tracking approach is capable of following the involuntary motion of the subject in the IR image sequence, thereby allowing us to track the temperature evolution for a particular region on the skin. In addition, to compensate for the measurement artifacts induced by the surface curvature in IR thermography, a correction formula was developed based on the emissivity model and phantom experiments. The correction formula was integrated into a 3D imaging procedure based on a system combining Kinect and IR cameras. We demonstrated the feasibility of mapping 2D IR images onto the 3D surface of the human body. The accuracy of temperature measurement was improved by applying the correction method. Finally, we designed a variety of quantitative approaches to analyze the clinical data acquired from patient studies of pigmented lesions and hemangiomas. These approaches allow us to evaluate the thermal signatures of lesions with different characteristics, measured in both static and dynamic IR imaging. The collection of methodologies described in this dissertation, leading to improved ease of use and accuracy, can contribute to the broader implementation of quantitative IR thermography in medical diagnostics

Experimental and Computational Analysis of Aerogels and Aerogel-Composites Under Different Environmental Conditions for Biomedical and Space Applications

Aerogels are highly porous and lightweight materials with a unique combination of physical and chemical properties that can be customized to fit the parameter space desired, for the application at hand. The number of applications that have enlisted the use of aerogels have grown substantially in recent years ranging from biomedicine to aerospace. This work investigates the interaction of aerogels and aerogel composites with its environment namely interaction with two types of incident waves: pressure waves and UV radiation. In the first case, the effect of aerogel porosity and stiffness on ultrasound wave propagation in an aqueous and a non-aqueous environment was explored. The detection, tracking, attenuation, and damping caused by aerogels was investigated both computationally and experimentally. Image analysis techniques for acoustic parameter extraction such as acoustic attenuation coefficient was developed. The motivation behind this work was to achieve a real time visualization of wave interactions with aerogels in the two different media mentioned earlier, using k wave tool, and by recording the regions of maximum and minimum pressure at the interfaces. Results indicate the relationship between the degree of attenuation, porosity, and material stiffness and can be applied to any combination of parameter space. In the second phase of the study, aerogel composites were exposed to direct UV radiation outside of the Earth’s atmosphere and the effect of the prolonged exposure (6 months) on the behavior of the composites was studied. Specifically, the effect of the radiation on the excitation/ emission behavior of thermographic phosphors coated on aerogels under low Earth orbit conditions. Investigating the effect of the radiation on the mechanical properties of the aerogels was not in the scope of this work and will not be discussed

Transient thermography for detection of micro-defects in multilayer thin films

Delamination and cracks within the multilayer structure are typical failure modes observed in microelectronic and micro electro mechanical system (MEMS) devices and packages. As destructive detection methods consume large numbers of devices during reliability tests, non-destructive techniques (NDT) are critical for measuring the size and position of internal defects throughout such tests. There are several established NDT methods; however, some of them have significant disadvantages for detecting defects within multilayer structures such as those found in MEMS devices. This thesis presents research into the application of transient infrared thermography as a non-destructive method for detecting and measuring internal defects, such as delamination and cracks, in the multilayer structure of MEMS devices. This technique works through the use of an infrared imaging system to map the changing temperature distribution over the surface of a target object following a sudden change in the boundary conditions, such as the application of a heat source to an external surface. It has previously been utilised in various applications, such as damage assessment in aerospace composites and verification of printed circuit board solder joint manufacture, but little research of its applicability to MEMS structures has previously been reported. In this work, the thermal behaviour of a multilayer structure containing defects was first numerically analysed. A multilayer structure was then successfully modelled using COMSOL finite element analysis (FEA) software with pulse heating on the bottom surface and observing the resulting time varying temperature distribution on the top. The optimum detecting conditions such as the pulse heating energy, pulse duration and heating method were determined and applied in the simulation. The influences of thermal properties of materials, physical dimensions of film, substrate and defect and other factors that will influence the surface temperature gradients were analytically evaluated. Furthermore, a functional relationship between the defect size and the resulting surface temperature was obtained to improve the accuracy of estimating the physical dimensions and location of the internal defect in detection. Corresponding experiments on specimens containing artificially created defects in macro-scale revealed the ability of the thermographic method to detect the internal defect. The precision of the established model was confirmed by contrasting the experimental results and numerical simulations

NASA Tech Briefs, February 1996

Topics covered include: Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Life Sciences; Books and Reports

APPLICATIONS OF HEAT AND MASS TRANSFER ANALYSIS IN BIO-MEDICINE AND MATERIALS

Heat and mass transfer analysis has its application in various fields including automobile, steam-electric power generation, energy systems, HVAC, electronic device cooling and in characterizing and diagnosing diseases. Here we have focused on applying the principles of heat and mass transfer to biological tissue and materials. In the first part we introduce a computational method to simultaneously estimate size, location and blood perfusion of model cancerous breast lesions from surface temperature data. A 2-dimensional computational phantom of axisymmetric tumorous breast with six tissue layers, epidermis, papillary dermis, reticular dermis, fat, gland, muscle layer and spherical tumor was used to generate surface temperature distributions and estimate tumor characteristics iteratively using an inverse algorithm based on the Levenberg-Marquardt method. However, similar steady state temperature profiles for different tumors are insufficient to simultaneously estimate blood perfusion, size and location of tumor. This becomes possible when transient temperature data are used along with steady state data. Thus, in addition to the steady state temperature data, we modified and expanded the inverse algorithm to include transient data that can be captured by dynamic infrared imaging. Blood perfusion is an indicator of the growth rate of the tumor and therefore its evaluation can lead to assessment of tumor malignancy. In the second part we treat X-ray computed tomography (CT) perfusion. The goal was to reduce the total radiation exposure by reducing the number of scans without compromising information integrity. CT scan images obtained from a rabbit model of liver and tumors were processed using the maximum slope (MS) method to estimate blood perfusion in the liver. Limitations of MS method are also discussed. The MS method makes use of key time points, forming the basis of the rationale to explore optimization strategies that utilize variable time intervals, rather than the more common approach of fixed time intervals. Results show that this leads to significant improvement, without compromising diagnostic information. In the last section we explore the magnetic shielding efficacy of superconducting materials and methods to mitigate the effect of necessary discontinuities in superconducting shield

Designing and Evaluating Next-Generation Thermographic Systems to Support Residential Energy Audits

Buildings account for 41% of primary energy consumption in the United States—more than any other sector—and contribute to an increasing portion of carbon dioxide emissions (33% in 1980 vs. 40% in 2009). To help address this problem, the U.S. Department of Energy recommends conducting energy audits to identify sources of inefficiencies that contribute to rising energy use. One effective technique used during energy audits is thermography. Thermographic-based energy auditing activities involve the use of thermal cameras to identify, diagnose, and document energy efficiency issues in the built environment that are visible as anomalous patterns of electromagnetic radiation. These patterns may indicate locations of air leakages, areas of missing insulation, or moisture issues in the built environment. Sensor improvements and falling costs have increased the popularity of this auditing technique, but its effectiveness is often mediated by the training and experience of the auditor. Moreover, given the increasing availability of commodity thermal cameras and the potential for pervasive thermographic scanning in the built environment, there is a surprising lack of understanding about people’s perceptions of this sensing technology and the challenges encountered by an increasingly diverse population of end-users. Finally, there are few specialized tools and methods to support the auditing activities of end-users. To help address these issues, my work focuses on three areas: (i) formative studies to understand and characterize current building thermography practices, benefits, and challenges, (ii) human-centered explorations into the role of automation and the potential of pervasive thermographic scanning in the built environment, and (iii) evaluations of novel, interactive building thermography systems. This dissertation presents a set of studies that qualitatively characterizes building thermography practitioners, explores prototypes of novel thermographic systems at varying fidelity, and synthesizes findings from several field deployments. This dissertation contributes to the fields of sustainability, computer science, and HCI through: (i) characterizations of the end-users of thermography, (ii) critical feedback on proposed automated thermographic solutions, (iii) the design and evaluation of a novel longitudinal thermography system designed to augment the data collection and analysis activities of end-users, and (iv) design recommendations for future thermographic systems