scholarly journals A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography

2021 ◽  
Vol 8 (12) ◽  
pp. 191
Author(s):  
Christos Dimas ◽  
Vassilis Alimisis ◽  
Nikolaos Uzunoglu ◽  
Paul P. Sotiriadis
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Bayesian Learning ◽  
Image Quality Assessment ◽  
Low Cost ◽  
Sparse Bayesian Learning ◽  
Method Of Moment ◽  
Reconstruction Problem ◽  
Impedance Tomography

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT’s exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object’s and the reconstruction domain’s geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs’ significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.

scholarly journals Multi-frame constrained block sparse Bayesian learning for flexible tactile sensing using electrical impedance tomography

2021 ◽  
Author(s):  
Xiaojie Wang
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Bayesian Learning ◽  
Reconstruction Algorithm ◽  
Tactile Sensor ◽  
Sensor System ◽  
Tactile Sensing ◽  
Contact Detection ◽  
Sparse Bayesian Learning ◽  
Impedance Tomography

In this paper, we presented a multi-frame constrained block sparse Bayesian learning (MFC-BSBL) reconstruction algorithm to tackle the challenge of poor-quality reconstruction images in electrical impedance tomography (EIT) for tactile sensing. The fundamental idea of MFC-BSBL is to explore the sparsity, intra-frame correlation, and inter-frame correlation of impedance distributions by extending the Bayesian inference framework. To verify the proposed algorithm, we conducted numerical simulations for different cases to identify one, multiple, round, and square targets. The simulation results demonstrated that this method can effectively detect the target positions and shapes by reducing artifacts and noise in the reconstructed images. To demonstrate the application of this approach to real EIT-based tactile sensing, we conducted real-contact detection experiments using the EIT tactile sensor system. Compared with traditional methods, the tactile sensor system using the MFC-BSBL algorithm can achieve accurate contact detection and significantly reduce artifacts and noise.

scholarly journals Multi-frame constrained block sparse Bayesian learning for flexible tactile sensing using electrical impedance tomography

2021 ◽  
Author(s):  
Xiaojie Wang
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Bayesian Learning ◽  
Reconstruction Algorithm ◽  
Tactile Sensor ◽  
Sensor System ◽  
Tactile Sensing ◽  
Contact Detection ◽  
Sparse Bayesian Learning ◽  
Impedance Tomography

In this paper, we presented a multi-frame constrained block sparse Bayesian learning (MFC-BSBL) reconstruction algorithm to tackle the challenge of poor-quality reconstruction images in electrical impedance tomography (EIT) for tactile sensing. The fundamental idea of MFC-BSBL is to explore the sparsity, intra-frame correlation, and inter-frame correlation of impedance distributions by extending the Bayesian inference framework. To verify the proposed algorithm, we conducted numerical simulations for different cases to identify one, multiple, round, and square targets. The simulation results demonstrated that this method can effectively detect the target positions and shapes by reducing artifacts and noise in the reconstructed images. To demonstrate the application of this approach to real EIT-based tactile sensing, we conducted real-contact detection experiments using the EIT tactile sensor system. Compared with traditional methods, the tactile sensor system using the MFC-BSBL algorithm can achieve accurate contact detection and significantly reduce artifacts and noise.

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

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.

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