Breast cancer recognition by electrical impedance tomography implemented with Gaussian relaxation-time distribution (EIT–GRTD)
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 d...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-08-01
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| Series: | Journal of Electrical Bioimpedance |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/joeb-2024-0011 |
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| Summary: | 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. |
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| ISSN: | 1891-5469 |