Enhanced imaging of piezoresistive nanocomposites through the incorporation of nonlocal conductivity changes in electrical impedance tomography

2018 ◽  
Vol 29 (9) ◽  
pp. 1850-1861 ◽  
Author(s):  
Hashim Hassan ◽  
Fabio Semperlotti ◽  
Kon-Well Wang ◽  
Tyler N Tallman
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Low Cost ◽  
Electrode Arrays ◽  
Sensitivity Matrix ◽  
Impedance Tomography ◽  
Ill Posed ◽  
Internal Conductivity ◽  
Tomography Inversion

Electrical impedance tomography is a method of noninvasively imaging the internal conductivity distribution of a domain. Because many materials exhibit piezoresistivity, electrical impedance tomography has considerable potential for application in structural health monitoring. Despite its numerous benefits such as being low cost, providing continuous sensing, and having the ability to be employed in real time, electrical impedance tomography is limited by several important factors such as the ill-posed nature of the inverse problem and the requirement for large electrode arrays to produce quality images. Unfortunately, current methods of mitigating these limitations impose upon the benefits of electrical impedance tomography. Herein, we propose a multi-physics approach of enhancing electrical impedance tomography without sacrificing any of its benefits. This approach is predicated on coupling global conductivity changes with the electrical impedance tomography inversion process thereby adding additional constraints and rendering the problem less ill-posed. Additionally, we leverage physically motivated global conductivity changes in the context of piezoresistive nanocomposites. We demonstrate this proof of concept with numerical simulations and demonstrate that by incorporating multiple conductivity changes, the rank of the sensitivity matrix can be improved and the quality of electrical impedance tomography reconstructions can be enhanced. The proposed method, therefore, has the potential of easing the implementation burden of electrical impedance tomography while concurrently enabling high-quality images to be produced without imposing on the major advantages of electrical impedance tomography.

scholarly journals A Krylov subspace type method for Electrical Impedance Tomography

2021 ◽  
Author(s):  
Mirjeta Pasha ◽  
Shyla Kupis ◽  
Sanwar Ahmad ◽  
Taufiquar Khan
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Krylov Subspace ◽  
Low Frequency ◽  
Small Dimension ◽  
Impedance Tomography ◽  
Type Method ◽  
Newton Algorithm ◽  
Ill Posed ◽  
Internal Conductivity

Electrical Impedance Tomography (EIT) is a well-known imaging technique for detecting the electrical properties of an object in order to detect anomalies, such as conductive or resistive targets. More specifically, EIT has many applications in medical imaging for the detection and location of bodily tumors since it is an affordable and non-invasive method, which aims to recover the internal conductivity of a body using voltage measurements resulting from applying low frequency current at electrodes placed at its surface. Mathematically, the reconstruction of the internal conductivity is a severely ill-posed inverse problem and yields a poor quality image reconstruction. To remedy this difficulty, at least in  part, we regularize and solve the nonlinear minimization problem by the aid of a Krylov subspace-type method for the linear sub problem during each iteration.  In EIT, a tumor or general anomaly can be modeled as a piecewise constant perturbation of a smooth background, hence, we solve the regularized problem on a subspace of relatively small dimension by the Flexible Golub-Kahan process that provides solutions that have sparse representation. For comparison, we use a well-known modified Gauss-Newton algorithm as a benchmark. Using simulations, we demonstrate the effectiveness of the proposed method. The obtained reconstructions indicate that the Krylov subspace method is better adapted to solve the ill-posed EIT problem and results in higher resolution images and faster convergence compared to reconstructions using the modified Gauss-Newton algorithm.

A Modified Landweber Iteration Algorithm using Updated Sensitivity Matrix for Electrical Impedance Tomography

2013 ◽  
Vol 5 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Lifeng Zhang
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Reconstructed Image ◽  
Iteration Algorithm ◽  
Sensitivity Matrix ◽  
Initial Image ◽  
Impedance Tomography ◽  
Static Test ◽  
Conductivity Distribution

Electrical impedance tomography (EIT) is a technique to reconstruct the conductivity distribution of an inhomogeneous medium by injecting currents at the boundary of an object and measuring the resulting changes in voltage. The sensitivity matrix of EIT is calculated with a selected reference conductivity distribution, which is time-consuming. However, the sensitivity matrix will change with the media distribution, which results in the quality of the reconstructed image reduction. A modified Landweber iterative algorithm based on updated sensitivity matrix was presented in this paper. The reconstructed image based on conventional Landweber iteration was selected as the initial image for sensitivity matrix update, and the reconstructed images after sensitivity matrix update using different initial images were compared. The effect on the quality of reconstructed images for different times of sensitivity matrix update was also analyzed. Simulation and static test were carried out. Experimental results showed that reconstructed images with higher quality can be obtained.

CALIBRATION OF A LOW COST ELECTRICAL IMPEDANCE TOMOGRAPHY SYSTEM WITH A RING OF RESISTORS AND A KCL SOLUTION

2019 ◽  
Author(s):  
Bruno Furtado de Moura ◽  
francisco sepulveda ◽  
Jorge Luis Jorge Acevedo ◽  
Wellington Betencurte da Silva ◽  
Rogerio Ramos ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Low Cost ◽  
Impedance Tomography ◽  
Tomography System

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
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Low Cost ◽  
Impedance Tomography

Patch-based sparse reconstruction for electrical impedance tomography

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Qi Wang ◽  
Pengcheng Zhang ◽  
Jianming Wang ◽  
Qingliang Chen ◽  
Zhijie Lian ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Sparse Representation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Inverse Operator ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Content Type ◽  
Ill Posed ◽  
High Level

Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity. Findings Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Originality/value EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

scholarly journals Low Cost Instrumentation for Electrical Impedance Tomography in Biomedical Applications

2015 ◽  
Author(s):  
Stewart Smith ◽  
Hancong Wu ◽  
Jiabin Jia
Keyword(s):  
Electrical Impedance Tomography ◽  
Integrated Circuit ◽  
Biomedical Applications ◽  
Electrical Impedance ◽  
Low Cost ◽  
Impedance Measurement ◽  
Impedance Tomography ◽  
Impedance Measurements ◽  
Additional Circuitry ◽  
Initial Results

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.

Using Extreme Learning Machines and the Backprojection Algorithm as an Alternative to Reconstruct Electrical Impedance Tomography Images

2021 ◽  
pp. 16-27
Author(s):  
Juliana Carneiro Gomes ◽  
Maíra Araújo de Santana ◽  
Clarisse Lins de Lima ◽  
Ricardo Emmanuel de Souza ◽  
Wellington Pinheiro dos Santos
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Imaging Techniques ◽  
Low Cost ◽  
Computational Cost ◽  
Extreme Learning Machines ◽  
Impedance Tomography ◽  
Learning Machines ◽  
Electrical Potentials ◽  
Reconstruction Methods

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.

scholarly journals Development a low-cost electrical impedance tomography system for non-invasively detecting abnormal in breast tissue - Phantom study-

10.29007/x6vj ◽  
2022 ◽  
Author(s):  
Minh Quan Cao Dinh ◽  
Quoc Tuan Nguyen Diep ◽  
Hoang Nhut Huynh ◽  
Ngoc An Dang Nguyen ◽  
Anh Tu Tran ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Low Cost ◽  
Impedance Tomography ◽  
Non Invasive ◽  
Tomography System ◽  
Tissue Phantom ◽  
Cost System ◽  
Invasive Method ◽  
Breast Tissues

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.

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