A Parallel Algorithmic Approach for Microwave Tomography in Breast Cancer Detection

Different technologies have been used for breast cancer detections clinically. But they have weaknesses in terms of sensitivity and specificity. Microwave imaging technique, on the contrary, 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 finite-difference 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. The execution time of the sequential algorithm (GA and FDTD combined) is 10,131 seconds. The total execution time obtained on 16 processors which is approximately 2000 seconds surpasses the sequential algorithm.