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Design of Multifrequency Electrical Impedance Tomography (MfEIT) Based on Analog Revelation for Breast Cancer Detection
This study aims to design Multifrequency Electrical Impedance Tomography (MfEIT) based on Analog Discovery to detect breast cancer. The MfEIT was built from Analog Discovery which can be used as a signal generator,power supply,voltage control,and measuring voltage and phase difference.
References:
- Lee,E., Erdene, M., seo, J. K. and Woo, E.J. 2012. URL
Electrical Impedance Tomography – Recent Applications and Developments
Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. Screening for breast cancer by EIT-MF, for a given physiological state, is based on the fact that each tissue has a particular conductivity and permittivity and can definitely help to differentiate this tissue from other tissues and physiological states of the same tissue.
References:
Multifrequency Electrical impedance Tomography (Mf-EIT) for the Detection of Breast Cancer phantom Anomalies
In brief, this study proposes an innovative Electrical Impedance Tomography (EIT). The designed and built the Mf-EIT hardware based on data reconstruction using Gauss-Newton and GREIT. The Electrical Impedance Tomography designed to detect the anomalies in the reconstructed image of Breast Cancer. The results obtained that frequency variations do not affect the conductivity of fantom anomaly. This is as fantom is made from agar material and NaCl solution that does not have a cell structure and composition like actual cancer tissue.
Conclusion
The conclusion of this study is the module Analog Discovery 2 Can be used to build a Tomographical System for Multifretion Electric Impedance (TIEM). The TIEM system that has been built has been successfully created and can be used for detection of breast cancer anomalies. Visually,the position and number of anomalies in the reconstruction image is in accordance with the position and number of anomalies in fantom.
Author: Dr. Khusnul Ain, ST, M.Sc.
Detailed Details
Detailed information from this research can be seen in our writing at:
Bayu Ariwanto, Rohadatul Aisya, Khusnul Ain, riries Rulaningtyas, Ahmad Hoirul Basori, nuril Ukhrowiyah, and Andi Besse Fidausiah Mansur, 2025, Multifrequency Electrical Impedance Tomography (MF-EIT) for the Detection of Breast Cancer Phantom Anomalies, Methodsx, Vol. 14, DOI: 10.1016/j.mex.2024.103087
https://linkinghub.elsevier.com/retrieve/pii/S2215016124005387
Designing Multifrequency Electrical impedance Tomography for Breast Cancer Detection: An Interview with Dr. Khusnul ain
Table of Contents
Electrical Impedance Tomography (EIT) is an emerging noninvasive imaging technique that holds great potential in the early detection of breast cancer.Recent advancements, particularly those involving multifrequency EIT (MfEIT) using Analog Finding 2, have shown promising results. World-Today-News.com recently had the opportunity too speak with Dr. Khusnul Ain, an expert in this field, to delve deeper into these innovative applications and the future of this technology.
Understanding Multifrequency Electrical Impedance Tomography
Multifrequency Electrical Impedance Tomography (MfEIT) is an advanced method of imaging that allows us to detect anomalies in tissues with high accuracy. By using different frequencies, we can better differentiate between various tissues and physiological states.
senior Editor: Could you please provide an overview of how MfEIT works and its primary applications in medical imaging?
Certainly. MfEIT operates by injecting low-level electrical currents into the body and measuring the resulting voltage differences. Each type of tissue has a unique electrical impedance, so by analyzing these measurements across multiple frequencies, we can generate images that highlight anomalies such as tumors. This method is particularly useful in breast cancer screening due to its non-invasive nature and low cost.
Senior Editor: How does MfEIT differ from traditional EIT methods?
Unlike traditional EIT, wich typically operates at a single frequency, MfEIT uses multiple frequencies. This allows for better discrimination between different tissue types and physiological states. As a notable example, variations in frequency can definitely help distinguish between benign and malignant tissues, providing more detailed and accurate imaging.
The Role of Analog Discovery in MfEIT
Senior Editor: Your study highlights the use of Analog Discovery 2 in building MfEIT systems. How has this tool facilitated your work in this area?
Analog Discovery 2 is an incredibly versatile tool. It functions as a signal generator, power supply, voltage control, and measuring unit for voltage and phase differences. This multitasking capability has substantially streamlined our research process, making it easier to design and implement MfEIT hardware for detecting breast cancer anomalies.
Senior Editor: Can you elaborate on the specific configurations and settings used in your research?
In our setup, we used the Analog Discovery 2 to generate and measure electrical currents at various frequencies. We employed data reconstruction methods such as Gauss-Newton and GREIT to interpret these measurements and generate reconstructed images. This dual approach has been critical in detecting and accurately mapping out anomalies in the phantom models used in our study.
Recent Findings and Implications
Senior Editor: What were the key findings from your recent study?
Our findings indicated that frequency variations did not significantly affect the conductivity of the phantom anomalies in our model. The phantom was made from agar and nacl solution, which lack the intricate cell structure of actual cancer tissue. Despite this, our MfEIT system successfully detected and mapped the anomalies, showing great promise for future applications.
futures and Conclusion
Senior Editor: Where do you see the future of MfEIT technology heading?
The future of MfEIT is extremely promising. As we refine our techniques and develop more complex hardware, we can expect even greater precision and accuracy in detecting tissue anomalies. We are also exploring ways to integrate AI into our data reconstruction algorithms to further enhance image clarity and detail.
Senior Editor: what advice would you give to researchers and students interested in this field?
I would advise them to stay curious and keep exploring new possibilities. This field is rapidly evolving, and innovation is key. Collaboration across different disciplines, such as electrical engineering, medical physics, and computer science, can lead to groundbreaking advancements that will ultimately benefit patients and improve healthcare outcomes.
Author: dr. Khusnul Ain, ST, M.Sc.
For detailed details, please refer to: Bayu Ariwanto, Rohadatul Aisya, Khusnul Ain, riries Rulaningtyas, Ahmad Hoirul Basori, nuril Ukhrowiyah, and Andi Besse Fidausiah Mansur, 2025, Multifrequency Electrical Impedance Tomography (MF-EIT) for the detection of Breast Cancer Phantom Anomalies, Methodsx, Vol. 14,DOI: 10.1016/j.mex.2024.103087
https://linkinghub.elsevier.com/retrieve/pii/S2215016124005387
