Parallel Fdtd and Parallel Ga for Microwave Tomography in Breast Cancer Detection

Asymptomatic screening methods are import to lower the mortality rate of breast cancer patients. Technologies available in clinics have weaknesses in terms of sensitivity and specificity. Microwave imaging technique uses the apparent dielectric property contrasts between different breast tissues at microwave frequencies and is a prospective direction to find small tumor at their early stage. Microwave tomography falls in one category of microwave imaging technique. There are two main components in microwave tomography to detect abnormalities in breasts: Genetic Algorithm (GA) and FiniteDifference Time-Domain (FDTD). Both GA and FDTD are time-consuming, but, they are data-parallel in nature. In this paper, we have designed a parallel framework for microwave tomography: parallel GA combined with parallel FDTD. The algorithms are implemented on distributed memory machines running MPI. It achieves a result of finding a 1.5cm tumor in a breast phantom of 12cm in diameter, with a speedup of 6.25 using 16 processors.