## Abstract Magnetic detection electrical impedance tomography (MDβEIT) produces images of conductivity from magnetic field measurements taken around the body. The illβconditioned nature of the MDβEIT inverse problem is improved by limiting the number of unknowns to be solved. In this article, a me
Image reconstruction incorporated with the skull inhomogeneity for electrical impedance tomography
β Scribed by Ansheng Ni; Xiuzhen Dong; Guosheng Yang; Feng Fu; Chi Tang
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 961 KB
- Volume
- 32
- Category
- Article
- ISSN
- 0895-6111
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β¦ Synopsis
The structural similarity of the head model affects the accuracy of forward solution to electrical impedance tomography (EIT). Generally, the four-concentric circle model (FCCM) is used as the head model, which ignores the inhomogeneous distribution of the conductivity of real skull. In order to decrease the errors caused by using FCCM, a more accurate head model named inhomogeneous skull model (ISM) has been proposed and a reconstruction algorithm incorporated with ISM has been developed for brain EIT. Simulation results have shown improvement in image quality and localization accuracy when using ISM. It is also suggested that the reconstructed image could be more sensitive to the location of bony sutures than to the variation of skull thickness. In conclusion, incorporating skull inhomogeneity into image reconstruction is an effective way to improve image quality and localization accuracy for brain EIT.
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## Abstract This paper introduces a new reconstruction algorithm for electrical impedance tomography. The algorithm assumes that there are two separate regions of conductivity. These regions are represented as eccentric circles. This new algorithm then solves for the location of the eccentric circl