Spatial resolution improvement of 3D EIT images by the shrinking sLORETA-FOCUSS algorithm

Dong, Guoya and Liu, Heshang and Bayford, Richard and Yerworth, Rebecca J. and Schimpf, Paul H. and Yan, Weili (2005) Spatial resolution improvement of 3D EIT images by the shrinking sLORETA-FOCUSS algorithm. Physiological Measurement, 26 (2). S199-S208. ISSN 0967-3334

Full text is not in this repository.

This item is available in the Library Catalogue

Abstract

This paper describes the use of the shrinking sLORETA-FOCUSS algorithm to improve the spatial resolution of three-dimensional (3D) EIT images. Conventional EIT yields inaccurate, low spatial resolution images, due to noise, the low sensitivity of boundary voltages to inner conductivity perturbations and a limited number of boundary voltage measurements. The focal underdetermined system solver (FOCUSS) algorithm produces a localized energy solution based on the weighted minimum-norm least-squares (MNLS) solution. It was successfully applied for the spatial resolution improvement of EIT images of simulated and tank data for a 2D homogeneous circular disc. However, due to the fact that a 3D mesh system contains many more elements, much more memory is required to store the weighting matrix. In order to extend the work to 3D, the shrinking-FOCUSS method is utilized to shrink the solution space as well as the weighting matrix in each iteration step. The solution of the standardized low resolution electromagnetic tomography algorithm (sLORETA) is adopted as the initial estimate of the shrinking-FOCUSS. The effectiveness is verified by implementing the new algorithm on tank data for a three-dimensional homogeneous sphere.

Item Type:Article
Research Areas:Science & Technology > Biomedical Science
Citations on ISI Web of Science:1
ID Code:2410
Useful Links:
Deposited On:21 May 2009 16:55
Last Modified:04 Feb 2014 07:16

Repository Staff Only: item control page

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year