Electrical Impedance Computed Tomography Based on a Finite Element Model

Murai, Tetsuya; Kagawa, Y.

doi:10.1109/tbme.1985.325526

Cited by 235 publications

(95 citation statements)

References 5 publications

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“…This choice was driven primarily by the requirements of the Sheffield backprojection algorithm (Barber and Seagar, 1987). However, it has continued to be used in new EIT designs, even though the regularized reconstruction approaches (developed since the work of Murai and Kagawa, 1985) are inherently agnostic of the details of the interface patterns. Of the recent EIT designs of which the authors are aware (both commercial and research), three quarters use the Sheffield protocol.…”

Section: Introductionmentioning

confidence: 99%

Adjacent stimulation and measurement patterns considered harmful

2011

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Abstract. We characterize the ability of electrical impedance tomography (EIT) to distinguish changes in internal conductivity distributions, and analyze it as a function of stimulation and measurement patterns. A distinguishability measure, z, is proposed which is related to the signal to noise ratio of a medium and to the probability of detection of conductivity changes in a region of interest. z is a function of the number of electrodes, the EIT stimulation and measurement protocol, the stimulation amplitude, the measurement noise, and the size and location of the contrasts. Using this measure we analyze various choices of stimulation and measurement patterns under the constraint of medical electrical safety limits (maximum current into the body). Analysis is performed for a planar placement of 16 electrodes for simulated 3D tank and chest shapes, and measurements in a saline tank. Results show that the traditional (and still most common) adjacent stimulation and measurement patterns have by far the poorest performance (by 6.9×). Good results are obtained for trigonometric patterns and for pair drive and measurement patterns separated by over 90 • . Since the possible improvement over adjacent patterns is so large, we present this result as a call to action: adjacent patterns are harmful, and should be abandoned. We recommend using pair drive and measurement patterns separated by one electrode less than 180 • . We describe an approach to modify an adjacent pattern EIT system by adjusting electrode placement.

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Section: Introductionmentioning

confidence: 99%

Adjacent stimulation and measurement patterns considered harmful

2011

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“…The basic theorem of sensitivity in Electrical Impedance Tomography can be presented as follows [8]:…”

Section: A Sensitivity and Forwards Problemmentioning

confidence: 99%

Monitoring Cleaning-In-Place by electrical resistance tomography with dynamic references

Wang

Yin

2016

2016 IEEE International Conference on Imaging Systems and Techniques (IST)

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Abstract-In multifunctional food and detergent production lines, accurate identification of ending point of the cleaning process for the previous product is crucial to ensure product integrity. In this paper, a commercial electrical resistance tomography system was applied to monitoring a lab Cleaning-In-Place circuit. Several image reconstruction algorithms are compared for the accurate identification of the end point and an optimized algorithm based on Tikhonov regularization with dynamic references is proposed and verified to be the best solution. The capabilities of this novel approach are discussed.

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“…Because the number of conductivity elements is much greater than the number of measurements, x is longer than y, and J is not square and therefore does not have an inverse. Instead, a linear reconstruction algorithm calculates an estimate of xx = Ry (2) using a reconstruction matrix R. Many algorithms to derive R have been proposed, four of which are used in this study: TSVD (truncated singular value decomposition [13], [14]), GREIT (Graz consensus Reconstruction algorithm for EIT [10]), and two variants of the one-step Gauss-Newton (GN) method. In the TSVD algorithm, R is the truncated pseudoinverse…”

Section: B Reconstruction Algorithmsmentioning

confidence: 99%

Impact of Model Shape Mismatch on Reconstruction Quality in Electrical Impedance Tomography

Grychtol

Lionheart

Bodenstein

et al. 2012

IEEE Trans. Med. Imaging

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Abstract-Electrical Impedance Tomography (EIT) is a lowcost, non-invasive and radiation free medical imaging modality for monitoring ventilation distribution in the lung. Although such information could be invaluable in preventing ventilatorinduced lung injury in mechanically ventilated patients, clinical application of EIT is hindered by difficulties in interpreting the resulting images. One source of this difficulty is the frequent use of simple shapes which do not correspond to the anatomy to reconstruct EIT images. The mismatch between the true body shape and the one used for reconstruction is known to introduce errors, which to date have not been properly characterized. In the present study we therefore seek to 1) characterize and quantify the errors resulting from a reconstruction shape mismatch for a number of popular EIT reconstruction algorithms and 2) develop recommendations on the tolerated amount of mismatch for each algorithm. Using real and simulated data, we analyze the performance of 4 EIT reconstruction algorithms under different degrees of shape mismatch. Results suggest that while slight shape mismatch is well tolerated by all algorithms, using a circular shape severely degrades their performance.

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Electrical Impedance Computed Tomography Based on a Finite Element Model

Cited by 235 publications

References 5 publications

Adjacent stimulation and measurement patterns considered harmful

Adjacent stimulation and measurement patterns considered harmful

Monitoring Cleaning-In-Place by electrical resistance tomography with dynamic references

Impact of Model Shape Mismatch on Reconstruction Quality in Electrical Impedance Tomography

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