A Methodology to Assist in Improvements of Low-cost Electrical Impedance Tomography Systems

2022 ◽  
Vol 20 (1) ◽  
pp. 141-152
Author(s):  
Bruno Furtado De Moura ◽  
Adriana Machado Malafaia Da Mata ◽  
Marcio Ferreira Martins ◽  
Francisco Hernan Sepulveda Palma ◽  
Rogerio Ramos
Author(s):  
Bruno Furtado de Moura ◽  
francisco sepulveda ◽  
Jorge Luis Jorge Acevedo ◽  
Wellington Betencurte da Silva ◽  
Rogerio Ramos ◽  
...  

Author(s):  
Stewart Smith ◽  
Hancong Wu ◽  
Jiabin Jia

This poster reports the design, implementation and testing of a portable and inexpensive bio-impedance measurement system intended for electrical impedance tomography (EIT) in cell cultures. The system is based on the AD5933 impedance analyser integrated circuit with additional circuitry to enable four-terminal measurement. Initial results of impedance measurements are reported along with an EIT image reconstructed using the open source EIDORS package.


Author(s):  
Juliana Carneiro Gomes ◽  
Maíra Araújo de Santana ◽  
Clarisse Lins de Lima ◽  
Ricardo Emmanuel de Souza ◽  
Wellington Pinheiro dos Santos

Electrical Impedance Tomography (EIT) is an imaging technique based on the excitation of electrode pairs applied to the surface of the imaged region. The electrical potentials generated from alternating current excitation are measured and then applied to boundary-based reconstruction methods. When compared to other imaging techniques, EIT is considered a low-cost technique without ionizing radiation emission, safer for patients. However, the resolution is still low, depending on efficient reconstruction methods and low computational cost. EIT has the potential to be used as an alternative test for early detection of breast lesions in general. The most accurate reconstruction methods tend to be very costly as they use optimization methods as a support. Backprojection tends to be rapid but more inaccurate. In this work, the authors propose a hybrid method, based on extreme learning machines and backprojection for EIT reconstruction. The results were applied to numerical phantoms and were considered adequate, with potential to be improved using post processing techniques.


10.29007/x6vj ◽  
2022 ◽  
Author(s):  
Minh Quan Cao Dinh ◽  
Quoc Tuan Nguyen Diep ◽  
Hoang Nhut Huynh ◽  
Ngoc An Dang Nguyen ◽  
Anh Tu Tran ◽  
...  

Electrical Impedance Tomography (EIT) is known as non-invasive method to detect and classify the abnormal breast tissues. Reimaging conductivity distribution within an area of the subject reveal abnormal tissues inside that area. In this work, we have created a very low-cost system with a simple 16-electrode phantom for doing research purposes. The EIT data were measured and reconstructed with EIDORS software.


2018 ◽  
Vol 44 (3) ◽  
pp. 2305-2320 ◽  
Author(s):  
Gurmeet singh ◽  
Sneh Anand ◽  
Brejesh Lall ◽  
Anurag Srivastava ◽  
Vaneet Singh

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Fei Yang ◽  
Jie Zhang ◽  
Robert Patterson

Electrical impedance tomography (EIT) has the potential to provide a low cost and safe imaging modality for clinically monitoring patients being treated with mechanical ventilation. Variations in reconstruction algorithms at different clinical settings, however, make interpretation of regional ventilation across institutions difficult, presenting the need for a unified algorithm for thoracic EIT reconstruction. Development of such a consensual reconstruction algorithm necessitates a forward model capable of predicting surface impedance measurements as well as electric fields in the interior of the modeled thoracic volume. In this paper, we present an anatomically realistic forward solver for thoracic EIT that was built based on high resolution MR image data of a representative adult. Accuracy assessment of the developed forward solver in predicting surface impedance measurements by comparing the predicted and observed impedance measurements shows that the relative error is within the order of 5%, demonstrating the ability of the presented forward solver in generating high-fidelity surface thoracic impedance data for thoracic EIT algorithm development and evaluation.


2021 ◽  
Vol 2008 (1) ◽  
pp. 012019
Author(s):  
Marcelo David ◽  
Omer Amran ◽  
Ron Simhi ◽  
Franco Simini

Abstract This work describes the theoretical basis of an electrical impedance tomography imaging system based on numerical analysis of the step response. Its novelty relies on the use of time domain for rendering the tomographic images. Following the injection of a Heaviside-step current through two electrodes, the voltage-response is measured on all couple of electrodes according to the neighbouring strategy; this process is repeated on every pair of consecutive electrodes. Based on the measurements, a tomographic image is reconstructed using the Gauss-Newton-Raphson algorithm. We tested the technique by simulating two representative circuits: one symmetrical pseudo-isotropic and one pseudo-anisotropic in AC, while both pseudo-isotropic at DC. The time-domain reconstructed images show the second network’s pseudo-anisotropy while allowing the system to show its tendency to pseudo-isotropy when the time elapses towards DC-steady-state. This novel technique for reconstructing electrical impedance tomographic images may shed new light on sensing slight differences in tissues while being fast and low-cost.


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