Toward understanding the complex mechanisms behind breast thermography: an overview for comprehensive numerical study

摘要: The abnormal thermogram has been shown to be a reliable indicator of high risk breast cancer. Nevertheless, a major weakness current infrared thermography is its poor sensitivity for deeper tumors. Numerical modeling for provides an effective tool investigate the complex relationships between thermal behaviors and underlying patho-physiological conditions. We have developed set new modeling techniques to take into account some subtle factors usually ignored in previous studies, such as gravity-induced elastic deformations of the breast, nonlinear elasticity soft tissues, dynamic behavior thermograms. Conventional "forward problem" modeling cannot used directly improve tumor detectability, however, because tissue thermal properties are generally unknown. Therefore, we propose "inverse problem" technique that aims estimate the thermal properties from surface thermogram. Our data suggest estimation tumor-induced thermal contrast can improved significantly by using proposed inverse problem solving to provide individual-specific background, especially expect methods, taken together, provide stronger foundation for, greater specificity precision in, thermographic diagnosis, and treatment,