Literature DB >> 11236878

Validation of a 3D reconstruction algorithm for EIT of human brain function in a realistic head-shaped tank.

A T Tidswell1, A Gibson, R H Bayford, D S Holder.   

Abstract

Previous work has demonstrated that electrical impedance tomography can be used to image human brain activity during evoked responses, but two-thirds of the reconstructed images fail to localize an impedance change to the expected stimulated cortical area. The localization failure may be caused by modelling the head as a homogenous sphere in the reconstruction algorithm. This assumption may lead to errors when used to reconstruct data obtained from the human head. In this study a 3D reconstruction algorithm, based on a model of the head as a homogenous sphere, was characterized by simulating the algorithm model, the head shape and the presence of the skull in saline-filled tanks. EIT images of a sponge, 14 cm3 volume with a resistivity contrast of 12%, were acquired in three different positions in tanks filled with 0.2% saline. In a hemispherical tank, 19 cm in diameter, the sponge was localized to within 3.4-10.7% of the tank diameter. In a head-shaped tank, the errors were between 3.1 and 13.3% without a skull and between 10.3 and 18.7% when a real human skull was present. A significant increase in localization error therefore occurs if an algorithm based on a homogeneous sphere is used on data acquired from a head-shaped tank. The increased error is due to the presence of the skull, as no significant increase in error occurred if a head-shaped tank was used without the skull present, compared to the localization error within the hemispherical tank. The error due to the skull significantly shifted the impedance change within the skull towards the centre of the image. Although the increased localization error due to the skull is not sufficient to explain the localization errors of up to 50% of the image diameter present in the images of some human subjects, the future use of a realistic head model in the reconstruction algorithm is likely to reduce the localization error in the human images due to the presence of the skull.

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Year:  2001        PMID: 11236878     DOI: 10.1088/0967-3334/22/1/321

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  7 in total

1.  Reducing boundary effects in static EIT imaging.

Authors:  Tzu-Jen Kao; Bong Seok Kim; D Isaacson; J C Newell; G J Saulnier
Journal:  Physiol Meas       Date:  2006-04-18       Impact factor: 2.833

2.  Magnetoacoustic tomography with magnetic induction (MAT-MI).

Authors:  Yuan Xu; Bin He
Journal:  Phys Med Biol       Date:  2005-10-19       Impact factor: 3.609

3.  A robust current pattern for the detection of intraventricular hemorrhage in neonates using electrical impedance tomography.

Authors:  T Tang; Sungho Oh; R J Sadleir
Journal:  Ann Biomed Eng       Date:  2010-03-18       Impact factor: 3.934

4.  A versatile high-permittivity phantom for EIT.

Authors:  Tzu-Jen Kao; Gary J Saulnier; David Isaacson; Tomas L Szabo; Jonathan C Newell
Journal:  IEEE Trans Biomed Eng       Date:  2008-11       Impact factor: 4.538

5.  A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2-D.

Authors:  S J Hamilton; C N L Herrera; J L Mueller; A Von Herrmann
Journal:  Inverse Probl       Date:  2012-07-31       Impact factor: 2.407

6.  Intracranial electrical impedance tomography: a method of continuous monitoring in an animal model of head trauma.

Authors:  Preston K Manwaring; Karen L Moodie; Alexander Hartov; Kim H Manwaring; Ryan J Halter
Journal:  Anesth Analg       Date:  2013-07-10       Impact factor: 5.108

7.  A novel 3D-printed head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution for electrical impedance tomography.

Authors:  Jie Zhang; Bin Yang; Haoting Li; Feng Fu; Xuetao Shi; Xiuzhen Dong; Meng Dai
Journal:  Sci Rep       Date:  2017-07-04       Impact factor: 4.379

  7 in total

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