Breast cancer is the most common cancer among women. Statistics released by American Cancer Society (1999) show that every 1 in every 8 women in the United States is likely to get breast cancer during her lifetime. Thermography, also known as thermal or infrared imaging, is a procedure to determine if an abnormality is present in the breast tissue temperature distribution, which may indicate the presence of an embedded tumor. In the year 1982, United States Food and Drug Administration (FDA) approved thermography as an adjunct method of detecting breast cancer, which could be combined with other established techniques like mammography. Although thermography is currently used to indicate the presence of an abnormality, there are no standard protocols to interpret the abnormal thermal images and determine the size and location of an embedded tumor. This research explores the relationship between the physical characteristics of an embedded tumor and the resulting temperature distributions on the skin surface. Experiments were conducted using a resistance heater that was embedded in agar in order to simulate the heat produced by a tumor in the biological tissue. The resulting temperature distribution on the surface was imaged using an infrared camera. In order to estimate the location and heat generation rate of the source from these temperature distributions, a genetic algorithm was used as the estimation method. The genetic algorithm utilizes a finite difference scheme for the direct solution of Pennes bioheat equation. It was determined that a genetic algorithm based approach is well suited for the estimation problem and that thermography can prove to be a valuable tool in locating tumors if combined with such an algorithm.

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