Electrical conductivity effect on the performance evaluation of EIT systems: A review

Mata, Adriana Machado Malafaia da; Moura, Bruno Furtado de; Martins, Márcio Ferreira; Palma, Francisco Hernán Sepúlveda; Ramos, Rogério

doi:10.1016/j.measurement.2021.109401

“…Applications Industry construction [7], process [9]- [14], material condition monitoring [15] Biomedical lung [5], [16]- [19], demodulation [20], heart [8], cell culture [21] Geophysics [3] Reconstruction quality methods [22]- [25], Machine learning methods [26],…”

Section: Type Articlesmentioning

confidence: 99%

Electrical Tomography Hardware Systems for Real-Time Applications: a Review

Meribout

¹

,

Khezzar

²

,

Alhammadi

³

et al. 2022

View full text Add to dashboard Cite

This paper presents a review of two-dimensional (2D) and three-dimensional (3D) electrical tomography (ET) hardware accelerators for real-time applications. While many recent review papers have discussed various algorithms for image reconstruction or acquisition systems, none of them has considered state-of-the-art hardware implementations of the associated image reconstruction algorithms to achieve real-time performance, especially for 3D ET where the computation requirement is excessively high. A 3D ET is useful in various applications such as robotics, autonomous vehicles, and process control, but it is computationally very expensive with respect to its 2D counterpart. Most implementations are based on single or multi-core CPUs and, to a lesser extent, on either graphics processing units (GPUs) or field programmable gate arrays (FPGAs). However, there is a clear gap between the currently available processors, whose computation power exceeds hundreds of teraflops per second (TOPS) at a reasonable low power consumption, and the ones recently used in ET systems. This gives great potential for nextgeneration ET systems to achieve real-time 2D and 3D ET reconstruction within a small form factor. The paper summarizes the most recent ET hardware systems with respect to their performance in terms of quality and processing frame rate, reconstruction methods, along with optimization and future directions.

show abstract

“…In order to solve the drawbacks of the conventional modalities, electrical impedance tomography (EIT) is an alternative to detect whole breast cancer [8,9] which is non-invasive [10] and provides realtime information that utilizes electrical current to measure conductivity changes, breast tissues crosssectional [11,12]. EIT explores electrical conductivity at various frequencies to monitor the human body [13] such as arm [14] and calf [15] compartments, gastric shape [16], albumin accumulation [17], and sodium imaging [18]. However, conventional EIT for breast cancer detection has shortcomings related to spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Detection of invasive ductal carcinoma in quadrant breast areas by electrical impedance tomography implemented with gaussian relaxation-time distribution (EIT-GRTD)

Setyawan,

Sejati,

Ogawa

et al. 2024

Biomed. Phys. Eng. Express

0

View full text Add to dashboard Cite

Invasive ductal carcinoma (IDC) in breast specimens has been detected in the quadrant breast area: (I) upper outer, (II) upper inner, (III) lower inner, and (IV) lower outer areas by electrical impedance tomography implemented with Gaussian relaxation-time distribution (EIT-GRTD). The EIT-GRTD consists of two steps which are (1) the optimum frequency f opt selection and (2) the time constant enhancement of breast imaging reconstruction. f opt is characterized by a peak in the majority measurement pair of the relaxation-time distribution function γ , which indicates the presence of IDC. γ represents the inverse of conductivity and indicates the response of breast tissues to electrical currents across varying frequencies based on the Voigt circuit model. The EIT-GRTD is quantitatively evaluated by multi-physics simulations using a hemisphere container of mimic breast, consisting of IDC and adipose tissues as normal breast tissue under one condition with known IDC in quadrant breast area II. The simulation results show that EIT-GRTD is able to detect the IDC in four layers at f opt = 30, 170 Hz. EIT-GRTD is applied in the real breast by employed six mastectomy specimens from IDC patients. The placement of the mastectomy specimens in a hemisphere container is an important factor in the success of quadrant breast area reconstruction. In order to perform the evaluation, EIT-GRTD reconstruction images are compared to the CT scan images. The experimental results demonstrate that EIS-GRTD exhibits proficiency in the detection of the IDC in quadrant breast areas while compared qualitatively to CT scan images.

show abstract

“…EIT has the capability to reconstruct conductivity particle distribution of a region of interest utilizing material conductivity properties [10] based on the electrical properties of the higher σ Cu than σ Al and σ Water . However, EIT has a drawback to detect the minor Cu particles due to detection on the outside of the sensitivity sensing area of EIT [11], which produces a weaker signal to detect the minor Cu particles, resulting in blurry images. Hence, in order to improve the image reconstruction quality of EIT, machine learning techniques were proposed.…”

Section: Introductionmentioning

confidence: 99%

Metal Particle Detection by Integration of a Generative Adversarial Network and Electrical Impedance Tomography (GAN-EIT) for a Wet-Type Gravity Vibration Separator

Ibrahim,

Sejati,

Darma

et al. 2023

Sensors

View full text Add to dashboard Cite

The minor copper (Cu) particles among major aluminum (Al) particles have been detected by means of an integration of a generative adversarial network and electrical impedance tomography (GAN-EIT) for a wet-type gravity vibration separator (WGS). This study solves the problem of blurred EIT reconstructed images by proposing a GAN-EIT integration system for Cu detection in WGS. GAN-EIT produces two types of images of various Cu positions among major Al particles, which are (1) the photo-based GAN-EIT images, where blurred EIT reconstructed images are enhanced by GAN based on a full set of photo images, and (2) the simulation-based GAN-EIT images. The proposed metal particle detection by GAN-EIT is applied in experiments under static conditions to investigate the performance of the metal detection method under single-layer conditions with the variation of the position of Cu particles. As a quantitative result, the images of detected Cu by GAN-EIT ψ̿GAN in different positions have higher accuracy as compared to σ*EIT. In the region of interest (ROI) covered by the developed linear sensor, GAN-EIT successfully reduces the Cu detection error of conventional EIT by 40% while maintaining a minimum signal-to-noise ratio (SNR) of 60 [dB]. In conclusion, GAN-EIT is capable of improving the detailed features of the reconstructed images to visualize the detected Cu effectively.

show abstract

Electrical conductivity effect on the performance evaluation of EIT systems: A review

Cited by 14 publications

References 66 publications

Electrical Tomography Hardware Systems for Real-Time Applications: a Review

Electrical Tomography Hardware Systems for Real-Time Applications: a Review

Detection of invasive ductal carcinoma in quadrant breast areas by electrical impedance tomography implemented with gaussian relaxation-time distribution (EIT-GRTD)

Metal Particle Detection by Integration of a Generative Adversarial Network and Electrical Impedance Tomography (GAN-EIT) for a Wet-Type Gravity Vibration Separator

Contact Info

Product

Resources

About