Breast Tumor Simulation and Parameters Estimation Using Evolutionary Algorithms

An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations

Exterior Means for Premature Recognition of Breast Cancer

This research is aimed at the early detection of breast cancer. Breast cancer is a form of cancer that is found in the breast tissue. Though mostly common in women, research has shown that it can also be diagnosed in men. The increasing trend in the mortality rate attributable to breast cancer can be traced to inefficient methods of detecting the cancer in its early stage. Current methods involve invasion, exposure of the patient to radiation, and/or compressing the breast. These may cause pain or even invest patient with other forms of ailments. In this work, infrared (IR) thermography has been deployed to detect breast cancer in its early stage. IR thermography uses IR radiation to measure heat patterns of human skin. It is passive in nature and it neither emit harmful radiation nor subject the patient to further risks. The thermograms captured by infrared camera are analysed by a software in stages, viz: extraction of region of interest, detection and masking of warm region among others. The resulting image in grayscale is sampled by comparing the white pixels (warm region) to the dark pixels (cool region). The software subsequently compares the outcome with a predefined threshold to predict the chances of occurrence of cancer and displays result for further diagnosis by medical expert. Our proposed modality is cost effective, safe and user friendly

An Investigation of Radiometer and Antenna Properties for Microwave Thermography

Microwave thermography obtains information about the subcutaneous body temperature by a spectral measurement of the intensity of the natural thermally generated radiation emitted by the body tissues. At lower microwave frequencies the thermal radiation can penetrate through biological tissue for significant distances. The microwave thermal radiation from inside the body can be detected and measured non-invasively at the skin surface by the microwave thermography technique, which uses a radiometer to measure the radiation which is received from an antenna on the skin. In the microwave region the radiative power received from a volume of material has a dependence on viewed tissue temperature T(r) of the form, where k is the Boltzmann's constant, B the measurement bandwidth, c(r) is the relative contribution from a volume element dv (the antenna weighting function). The weighting function, c(r), depends on the structure and the dielectric properties of the tissue being viewed, the measurement frequency and the characteristics of the antenna. In any practical radiometer system the body microwave thermal signal has to be measured along with a similar noise signal generated in the radiometer circuits. The work described in this thesis is intended to lead to improvement in the performance of microwave thermography equipment through investigations of antenna weighting functions and radiometer circuit noise sources. All work has been carried out at 3.2 GHz, the central operating frequency of the existing Glasgow developed microwave thermography system. The effects of input circuit losses on the operation of the form of Dicke radiometer used for the Glasgow equipment have been investigated using a computational model and compared with measurements made on test circuits. Very good agreement has been obtained for modelled and measured behaviour. The losses contributed by the microstrip circuit structure, that must be used in the radiometer at 3.2 GHz, have been investigated in detail. Microwave correlation radiometry, by "add and square" method, has been applied to the received signals from a crossed-pair antenna arrangement, the antennas being arranged to view a common region at a certain depth. The antenna response has been investigated using a noise source and by the nonresonant perturbation technique. The received pattern formed by the product of the individual antenna patterns gives a maximum depth in phantom dielectric material. The depth can be adjusted by changing the spacing of the antennas and the phase in an antenna path. However, the pattern is modulated by a set of positive and negative interference fringes so that the complete receive pattern has a complicated form. On uniform temperature distributions the total radiometric signal is zero with the positive and negative contributions cancelling each other out. The fringe modulation can be removed by placing the antennas close enough together, The pattern is then simple and gives a modest maximum response at a known depth in a known material. The radiometer system remains sensitive to the temperature gradients only and the wide range of dielectric properties and tissue structures in the region being investigated usually makes the system response difficult to interpret. For crossed-pair antennas in phase the effective penetration depth in high-and medium-water content tissues is about 2.5 cm at a frequency of 3.2 GHz. The field pattern observed was of the form expected from the measurements of the individual antenna behaviour with the appropriate interference pattern superimposed. The nonresonant perturbation technique has been developed and applied to assist the development of the medical application of both microwave thermographic temperature measurement and microwave hyperthermia induction. These techniques require the electromagnetic field patterns of the special antennas used to be known. These antennas are often formed by short lengths of rectangular or cylindrical waveguide loaded with a low-loss dielectric material to achieve good coupling to body tissues. The high microwave attenuation in biological materials requires the field configurations to be measured close to the antenna aperture in the near-field wave. The nonresonant perturbation is a simple technique which can be used to measure electromagnetic fields in lossy material close to the antenna. It has been applied here to measure accurately the antenna weighting function and the effective penetration depth in tissue simulating dielectric phantom materials. (Abstract shortened by ProQuest.)

Classification and Decision Making of Medical Infrared Thermal Images

Medical infrared thermal imaging (MITI) is a technique that allows safe and non-invasive recording of skin surface temperature distribution. The images gained provide underlining physiological information on the blood flow, vasoconstriction/vasodilatation, inflammation, transpiration or other processes that can contribute to skin temperature. This medical imaging modality has been available for nearly six decades and has proved to be useful for vascular, neurological and musculoskeletal conditions. Since the recordings are digital, in the form of a matrix of numbers (image), it can be computationally analyzed by a specialist mainly performing processing and analysis operations manually supported by proprietary software solutions. This limits the number of images that can be processed, making difficult for knowledge to evolve, expertise to develop and information to be shared. This chapter aims to disclose the medical imaging method, along with its particularities, principles, applications, advantages and disadvantages. The chapter introduces all available classification and decision making methods that can be employed using digital information, together with a literature review of their operation in the biomedical applications of infrared thermal imaging.info:eu-repo/semantics/publishedVersio

Development of Computer Modelling Techniques for Microwave Thermography

Microwave thermography obtains information about the temperature of internal body tissues by a spectral measurement of the intensity of the natural thermally generated radiation emitted by the body tissues. At the lower microwave frequencies radiation can penetrate through tissue for distances useful for a range of medical applications. Radiation from inside the body may be detected and measured non-invasively at the skin surface by a microwave thermography system consisting of a suitable antenna to detect the radiation and a radiometer receiver to measure its intensity. In the microwave region the radiative power emitted per unit bandwidth is proportional to the temperature of the emitting tissue and the total radiative power received from the body tissues, P, is a weighted volume average of temperature P = kB ∫w(r) T(r) dV where k is Boltzmann's constant, B is the bandwidth, T(r) is the temperature at the position r and w(r) is the weighting function. The weighting function depends on the structure and dielectric properties of the tissues being viewed, the measurement frequency and the characteristics of the antenna. The Glasgow developed microwave thermography system operates at a central frequency of 3.2 GHz, chosen to give the optimum compromise between the depth from which radiation may be received, which decreases with increasing frequency, and the lateral spatial resolution which increases with increasing frequency. A Dicke configuration radiometer receiver and a cylindrical low-impedance waveguide antenna, which operates in contact with the skin surface, are used. The output from the radiometer is calibrated to degrees Celsius to give a "microwave temperature" of the tissues being viewed. The tissue temperature distribution, T(r), reflects the vascular and metabolic state of the tissue. Diseases which affect these physiological functions will result in changes in the tissue temperature and hence in the measured microwave temperature. It is not possible, however, to solve the indirect problem of retrieval of the temperature distribution in the tissue from a single frequency measurement of microwave temperature. It is therefore necessary to model the temperature distribution in the tissue and, from this, solve the direct problem of calculation of the microwave temperature. Measured microwave temperatures may then be compared with those modelled to indicate the physiological state of the tissue. Pennes (1948) The temperature distribution in the tissue may be determined by solution of the steady-state heat transfer equation KV2T +Wbcb(Ta -T) + Q = 0 where K is the thermal conductivity of the tissue, Wb is the perfusion rate of blood through the tissue, cb is the specific heat capacity of the blood, Ta is the arterial blood temperature and Q is the rate of metabolic heat generation in the tissue. The boundary condition of heat loss at the skin surface is governed by the equation K dT/dn= h(T-Te ) where Te is the ambient temperature and h is the heat transfer coefficient due to the combined effects of heat loss by radiation, convection and evaporation. The microwave temperature may be calculated from the modelled temperature distribution and use of plane wave theory to determine the weighting function, with an increased power attenuation constant to account for the response of the antenna. The modelling of the tissue is simplified by the fact that both the tissue thermal conductivity and the microwave dielectric properties of the tissue depend primarily on the water content of the tissue. This thermal and electromagnetic modelling has been carried out to determine the expected microwave temperature profiles across the female breast. Microwave and infra-red temperature measurements were made on a group of young, normal women and a group of older, post-menopausal women with breast disease. In general the younger women will have higher water content breast tissue than that of the older women due to the higher proportion of glandular and connective tissue and the smaller proportion of low water content fat tissue

Breast Tumor Simulation and Parameters Estimation Using Evolutionary Algorithms

An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations

A study of the use of combined thermal and microwave modelling of body regions for microwave thermography

Microwave thermography has been used for the objective assessment of inflammation in the knee joints and wrist and finger joints of patients suffering with rheumatoid arthritis by comparison with similar information obtained from a control group of subjects. Combined microwave and thermal modelling has been used to estimate the effective blood supply to the anterior intra-articular region of the patella, and the perfusion of the quadriceps muscle in both groups. 2-D numerical modelling was compared with results obtained using 1-D modelling. Microwave thermography has also been used for the detection of breast cancer. However, problems such as high false positive detection rates have occurred due to natural cyclical breast temperature changes. The thermal behaviour of the normal breast throughout the menstrual cycle has been investigated and it is shown that microwave thermography is capable of detecting temperature variations in the female breast corresponding to the ovulatory and luteal phase of the menstrual cycle. Combined microwave and thermal modelling estimated the effective perfusion of the normal breast to be in the range 0.2 - ˜ 2 kg m-3s-1. This is consistent with previous work. Microwave thermography is a quick, simple technique which clinicians can easily use. It is non-invasive, passive and causes the patient no distress. By using combined microwave and thermal modelling it is possible to estimate tissue blood perfusions and water contents and compare them with expected values. The technique has many potential applications and will hopefully find a secure niche in clinical medicine

Infrared Thermography for Temperature Measurement and Non-Destructive Testing

The intensity of the infrared radiation emitted by objects is mainly a function of their temperature. In infrared thermography, this feature is used for multiple purposes: as a health indicator in medical applications, as a sign of malfunction in mechanical and electrical maintenance or as an indicator of heat loss in buildings. This paper presents a review of infrared thermography especially focused on two applications: temperature measurement and non-destructive testing, two of the main fields where infrared thermography-based sensors are used. A general introduction to infrared thermography and the common procedures for temperature measurement and non-destructive testing are presented. Furthermore, developments in these fields and recent advances are reviewed

The Use of Liquid Crystal Thermography in Selected Technical and Medical Applications—Recent Development

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Jan Stasiek et al. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. Thermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLC at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make the temperature and velocity fields in liquids visible by the simple expedient of directly mixing the liquid crystal material into the liquid (water, glycerol, glycol, and silicone oils) in very small quantities to use as thermal and hydrodynamic tracers. In biomedical situations, e.g., skin diseases, breast cancer, blood circulation and other medical application, TLC and image processing are successfully used as an additional non-invasive diagnostic method especially useful for screening large groups of potential patients. The history of this technique is reviewed, principal methods and tools are described and some examples are presented. Also steady-state and transient liquid crystal thermography (LCT) is used to measure local heat transfer on a plate equipped with transverse vortex generators. Automated evaluation allows determining the heat transfe