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Dual modality electrical impedance and ultrasound reflection tomography to improve image quality Cover

Dual modality electrical impedance and ultrasound reflection tomography to improve image quality

Open Access
|Apr 2017

Abstract

Electrical impedance tomography (EIT) is relatively new. It is a verypromising technique to be developed especially in the medical field. The advantages of EIT are that it is non-ionizing, simple, and portable and that it produces a high contrast image. Unfortunately, this modality does not have the capability to generate a highresolution image. Almost all imaging modalities has both advantages and disadvantages. Combining one modality with another is hence expected to cover the weaknesses of each other. The problem is how to develop the concepts, measurement systems and algorithm of dual modalities, particularly electrical and acoustical. The electrical modality can produce high contrast and the acoustical modality can produce high resolution. Combination of these will enhance the image resolution of EIT. High image resolution from the ultrasound reflection tomography is used as the prior information to improve the image resolution of the EIT. Finite Element Model (FEM) can be arranged by non-uniform elements, which are adapted to the boundary. Element models with higher density are arranged at the boundaries to obtain improvements of resolution and the model elements with lower density arranged at other locations to reduce the computational cost. The dual modality EIT with Ultrasound Reflection (EIT-UR) can produce high resolution and contrast image. The resolution improvement can also accelerate the convergence of the Newton-Raphson reconstruction methods.

DOI: https://doi.org/10.5617/jeb.3852 | Journal eISSN: 1891-5469
Language: English
Page range: 3 - 10
Submitted on: Sep 4, 2016
Published on: Apr 17, 2017
Published by: University of Oslo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2017 K. Ain, D. Kurniadi, S. Suprijanto, O. Santoso, published by University of Oslo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.