Back-projection distortions in applied potential tomography images due to non-uniform reference conductivity distributions

Avis, Nicholas John; Barber, D C; Brown, Brian; Kiber, Md. Adnan

doi:10.1088/0143-0815/13/a/022

Cited by 15 publications

(8 citation statements)

References 3 publications

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“…The skull acts as a high impedance barrier to current flow, so that a large proportion of current will pass through the path of least resistance within the scalp and a smaller proportion of the applied current will enter the brain. The presence of the skull is expected to attenuate the measured impedance change by a factor of perhaps five (Gibson et al, 2000;Joy et al, 1999) and distort the EIT images so that impedance changes are imaged more centrally than their true position, if the model for the reconstruction algorithm is a homogeneous sphere (Avis et al, 1992;Tidswell et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Electrical Impedance Tomography of Human Brain Activity

et al. 2001

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Section: Introductionmentioning

confidence: 99%

Three-Dimensional Electrical Impedance Tomography of Human Brain Activity

et al. 2001

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“…Existing reconstruction algorithms using excitation of adjacent electrodes to image the above impedance changes do not have sufficient sensitivity, owing to the skull's resistivity. The discontinuity between the skull and the more conductive tissues produces distortions in the isopotential paths, which limits the accuracy and spatial resolution of the reconstructed image (Avis et al 1992). The distorted isopotential paths produce a discrepancy between the true positions of impedance changes and their location in the reconstructed image.…”

Section: Introductionmentioning

confidence: 99%

“…The distorted isopotential paths produce a discrepancy between the true positions of impedance changes and their location in the reconstructed image. Simple correction of backprojection paths has not yielded successful results (Avis et al 1992). It may be possible to overcome this problem by using intracranial electrodes in epilepsy patients (Holder 1993).…”

Section: Introductionmentioning

confidence: 99%

Improvement of the positional accuracy of EIT images of the head using a Lagrange multiplier reconstruction algorithm with diametric excitation

et al. 1996

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A novel algorithm for the reconstruction of dynamic images using diametric excitation has been developed. The algorithm is specifically designed to image impedance changes in the brain using boundary data obtained from scalp electrodes by incorporating a priori information. The a priori information is obtain by solving the forward problem using a finite-element model (FEM) which includes the discontinuity of the skull resistivity. The advantages with this new approach are that the sensitivity and accuracy of the location of the impedance changes are improved compared to methods based on adjacent excitation.

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“…It should be noted that there are only twice opposite excitations, while in [18], the cycle current excitations pattern of adjacent excitation is applied, so the quality of this reconstructed images is different from that in [18]. The fourth column shows the images reconstructed by the LBP algorithm [26] whose difference sensitivity matrices are based on the reference and measured field. The performance index without noise is demonstrated in figure 13.…”

Section: Simulation Resultsmentioning

confidence: 99%

Difference sensitivity matrix constructed for ultrasound modulated electrical resistance tomography

Zhang

Dong

2018

Meas. Sci. Technol.

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Based on acousto-electric modulation, ultrasound modulated electrical resistance tomography (UMERT) is expected to provide high spatial resolution by extracting more information about the conductivity distribution from data enriched by coupling impedance measurements to localized mechanical vibrations. A difference sensitivity matrix constructed from reference and the measured field is proposed for UMERT. Firstly, the difference sensitivity matrix, related to conductivity information of the measured field, can suppress the adverse influences of soft-field effects on image reconstruction, which usually causes relatively large errors in traditional electrical resistance tomography (ERT) image reconstruction. Secondly, the differential form adopted by the proposed sensitivity matrix reduces the effect of the feature of the nonlinearity of the electric field on the distribution of the sensitivity matrix, which is reflected in sensitivity with a relatively low value in the central area whilst with a high value in the boundary area. Finally, the differential form can also reduce the influences of systematic errors on measurement data and thus, further improve the spatial resolution of reconstructed images. In addition, three current excitation patterns are discussed in order to obtain the best sensitivity of boundary voltage variations to conductivity changes. The proposed sensitivity matrix and the corresponding reconstructed image results are compared with that based on Geselowitz’s sensitivity theorem in ERT and one constructed from the measured field in UMERT. Both theory and simulation results verify the feasibility of the proposed difference sensitivity matrix. The reconstructed images demonstrate higher spatial resolution, especially for the detection of small objects. It also has a stronger ability in identifying the size of the objects and noise immunity.

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Back-projection distortions in applied potential tomography images due to non-uniform reference conductivity distributions

Cited by 15 publications

References 3 publications

Three-Dimensional Electrical Impedance Tomography of Human Brain Activity

Three-Dimensional Electrical Impedance Tomography of Human Brain Activity

Improvement of the positional accuracy of EIT images of the head using a Lagrange multiplier reconstruction algorithm with diametric excitation

Difference sensitivity matrix constructed for ultrasound modulated electrical resistance tomography

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