Breast cancer recognition by electrical impedance tomography implemented with Gaussian relaxation-time distribution (EIT–GRTD)

Abstract

The comparison between breast cancer recognition by electrical impedance tomography implemented with Gaussian relaxation time distribution (EIT-GRTD) and conventional EIT has been conducted to evaluate the optimal frequency for cancer detection fcancer. The EIT-GRTD has two steps, which are 1) the determination of the fcancer and 2) the refinement of breast reconstruction through time-constant enhancement. This paper employs two-dimensional numerical simulations by a finite element method (FEM) software to replicate the process of breast cancer recognition. The simulation is constructed based on two distinct electrical properties, which are conductivity σ and permitivitty ε, inherent to two major breast tissues: adipose tissues, and breast cancer tissues. In this case, the σ and ε of breast cancer σcancer, εcancer are higher than adipose tissues σadipose, εadipose. The simulation results indicate that the most effective frequency for breast cancer detection based on EIT-GRTD is fcancer = 56,234 Hz. Meanwhile, conventional EIT requires more processing to determine the fcancer based on image results or spatial conductivity analysis. Quantitatively, both EIT-GRTD and conventional EIT can clearly show the position of the cancer in layers 1 and 2 for EIT-GRTD and only layer 1 for conventional EIT.

Keywords

• breast cancer
• impedance
• tomography
• recognition
• gaussian relaxation-time distribution