scholarly journals Functional magnetic resonance electrical impedance tomography (fMREIT) sensitivity analysis using an active bidomain finite-element model of neural tissue

2018 ◽  
Vol 81 (1) ◽  
pp. 602-614 ◽  
Author(s):  
Rosalind J. Sadleir ◽  
Fanrui Fu ◽  
Munish Chauhan
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Magnetic Resonance ◽  
Finite Element Model ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Neural Tissue ◽  
Element Model ◽  
Functional Magnetic Resonance ◽  
Impedance Tomography

scholarly journals Evaluation of Thoracic Equivalent Multiport Circuits Using an Electrical Impedance Tomography Hardware Simulation Interface

Technologies ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 58
Author(s):  
Christos Dimas ◽  
Vassilis Alimisis ◽  
Ioannis Georgakopoulos ◽  
Nikolaos Voudoukis ◽  
Nikolaos Uzunoglu ◽  
...  
Keyword(s):  
Finite Element ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Imaging Modality ◽  
Low Cost ◽  
Element Model ◽  
High Temporal Resolution ◽  
Thoracic Impedance ◽  
Impedance Tomography ◽  
Signal Sampling

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography can be a valuable tool for monitoring patients. However, this technique is very sensitive to measurement noise or possible minor signal errors, coming from either the hardware, the electrodes, or even particular biological signals. Thus, the design of a good performance electrical impedance tomography hardware setup which properly interacts with the tissue examined is both an essential and a challenging concept. In this paper, we adopt an extensive simulation approach, which combines the system’s analogue and digital hardware, along with equivalent circuits of 3D finite element models that represent thoracic cavities. Each thoracic finite element model is created in MATLAB based on existing CT images, while the tissues’ conductivity and permittivity values for a selected frequency are acquired from a database using Python. The model is transferred to a multiport RLC network, embedded in the system’s hardware which is simulated at LT SPICE. The voltage output data are transferred to MATLAB where the electrical impedance tomography signal sampling and digital processing is also simulated. Finally, image reconstructions are performed in MATLAB, using the EIDORS library tool and considering the signal noise levels and different electrode and signal sampling configurations (ADC bits, sampling frequency, number of taps).

scholarly journals Electrical Impedance Tomography Based on Mixed Finite Element Model

2018 ◽  
Author(s):  
Agah D. Garnadi
Keyword(s):  
Finite Element ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Mixed Finite Element ◽  
Element Model ◽  
Element Formulation ◽  
Reconstruction Algorithms ◽  
Electrical Measurements ◽  
Impedance Tomography ◽  
Conductivity Distribution

Electrical Impedance Tomography (EIT) is a non-invasive imaging technology to map the conductivity distribution of material within confined device from electrical measurements made on the device periphery. The reconstruction of the conductivity distribution images is an inverse problem, which is ill-posed, hence is both extremely sensitive to noise and highly computationally intensive. This paper examines an EIT device based on Mixed Finite Element formulation model. The reconstruction algorithms of images based upon a non-linear least squares criteria.

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