Open Access

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

Galih Setyawan

Galih Setyawan

  • Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba UniversityChiba, Japan
  • Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah MadaYogyakarta, Indonesia
Search for this author on
Sciendo|Google Scholar
Setyawan, Galih
, 
Prima Asmara Sejati

Prima Asmara Sejati

  • Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba UniversityChiba, Japan
  • Department of Electrical Engineering and Informatics, Vocational College, Universitas Gadjah MadaYogyakarta, Indonesia
Search for this author on
Sciendo|Google Scholar
Sejati, Prima Asmara
, 
Kiagus Aufa Ibrahim

Kiagus Aufa Ibrahim

Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba UniversityChiba, Japan
Search for this author on
Sciendo|Google Scholar
Ibrahim, Kiagus Aufa
 and 
Masahiro Takei

Masahiro Takei

Department of Mechanical Engineering, Graduate School of Science and Engineering, Chiba UniversityChiba, Japan
Search for this author on
Sciendo|Google Scholar
Takei, Masahiro
  
Aug 12, 2024
Breast cancer recognition by electrical impedance tomography implemented with Gaussian relaxation-time distribution (EIT–GRTD)'s Cover Image
About this article
Previous Article
Next Article
Cite
Download Cover
Published Online: Aug 12, 2024
Page range: 99 - 106
Received: May 02, 2024
DOI: https://doi.org/10.2478/joeb-2024-0011
Keywords
© 2024 Galih Setyawan et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig.1:

Overview of breast cancer recognition by EIT-GRTD versus conventional EIT
Overview of breast cancer recognition by EIT-GRTD versus conventional EIT

Fig. 2:

Simulation setup of breast cancer recognition in the case of (a) z-axis view, and (b) y-axis view
Simulation setup of breast cancer recognition in the case of (a) z-axis view, and (b) y-axis view

Fig. 3:

Electrical properties utilized in the simulation [24].
Electrical properties utilized in the simulation [24].

Fig. 4:

Adjacent pattern in simulation [25]
Adjacent pattern in simulation [25]

Fig. 5:

The determination of the frequency for cancer detection fcancer in the simulation study
The determination of the frequency for cancer detection fcancer in the simulation study

Fig. 6:

Image reconstruction result by time constant enhancement breast imaging at fcancer = 56,234 Hz and conventional EIT
Image reconstruction result by time constant enhancement breast imaging at fcancer = 56,234 Hz and conventional EIT

Fig.7:

Absolute impedance |Z| and spatial mean conductivity 〈σ〉 plot in all layers
Absolute impedance |Z| and spatial mean conductivity 〈σ〉 plot in all layers
Language:
English
Publication timeframe:
1 times per year
Journal Subjects:
Engineering, Bioengineering and Biomedical Engineering, Biomedical Electronics, Life Sciences, Biophysics, Medicine, Biomedical Engineering, Physics, Spectroscopy and Metrology
Journal RSS Feed