Thermal modeling for breast tumor detection using thermography

The paper aims to complement thermography with numerical analysis in order to use patients' personalized data such as precise breast geometry and temperature patterns to detect tumors inside the breast. Previous studies in the literature use idealized semi-spherical breast models without experimental validation and personalized data. To improve the accuracy and reliability of computer-aided diagnosis of breast tumors, this study uses realistic 3D breast geometry, based on 3D scanning, in its numerical model, which is then validated by experiments through fabricating the breast using 3D printing and molding. It is shown in the combined numerical and experimental study that breast geometry is very important in determining the temperature field and detecting the tumor inside the breast. Further computational study shows that for breasts with and without tumors for cup sizes ranging from 120 to 260 mm and tumor depth from 5 to 25 mm, the maximum differences in surface temperatures can range from 0.34 to 1.37 degrees C. The difference become insignificant with large cup sizes. Thus, it can be concluded that the major important factors for precision tumor detection are tumor depth and breast geometry.