Thermal imaging is an emerging method for early detection of female breast tumor. The main challenge for thermal
imaging used in breast clinics lies in how to detect or locate the tumor and obtain its related parameters. The purpose of
this study is to apply an improved method which combined a genetic algorithm with finite element thermal analysis to determine the breast tumor and its parameters, such as the size, location, metabolic heat generation and blood perfusion rate. A finite element model for breast embedded a tumor was used to investigate the temperature distribution, and then the influences of tumor metabolic heat generation, tumor location and tumor size on the temperature were studied by use of an improved genetic algorithm. The results show that thermal imaging is a potential and effective detection tool for early breast tumor, and thermal simulation may be helpful for the explanation of breast thermograms.
The temperature of human body on the surface of the skin depends on the metabolic activity, the blood flow, and the
temperature of the surroundings. Any abnormality in the tissue, such as the presence of a tumor, alters the normal
temperature on the skin surface due to increased metabolic activity of the tumor. Therefore, abnormal skin temperature
profiles are an indication of diseases such as tumor or cancer. This study is to present an approach to detect the female
breast tumor and its related parameter estimations by combination the finite element method with infrared thermography
for the surface temperature profile. A 2D simplified breast embedded a tumor model based on the female breast
anatomical structure and physiological characteristics was first established, and then finite element method was used to
analyze the heat diffuse equation for the surface temperature profiles of the breast. The genetic optimization algorithm
was used to estimate the tumor parameters such as depth, size and blood perfusion by minimizing a fitness function
involving the temperature profiles simulated data by finite element method to the experimental data obtained by infrared
thermography. This preliminary study shows it is possible to determine the depth and the heat generation rate of the
breast tumor by using infrared thermography and the optimization analysis, which may play an important role in the
female breast healthcare and diseases evaluation or early detection. In order to develop the proposed methodology to be
used in clinical, more accurate anatomy 3D breast geometry should be considered in further investigations.
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