S J Hamilton1, W R B Lionheart, A Adler. 1. Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, WI 53233, United States of America.
Abstract
OBJECTIVE: To compare D-bar difference reconstruction with regularized linear reconstruction in electrical impedance tomography. APPROACH: A standard regularized linear approach using a Laplacian penalty and the GREIT method for comparison to the D-bar difference images. Simulated data was generated using a circular phantom with small objects, as well as a 'Pac-Man' shaped conductivity target. An L-curve method was used for parameter selection in both D-bar and the regularized methods. MAIN RESULTS: We found that the D-bar method had a more position independent point spread function, was less sensitive to errors in electrode position and behaved differently with respect to additive noise than the regularized methods. SIGNIFICANCE: The results allow a novel pathway between traditional and D-bar algorithm comparison.
OBJECTIVE: To compare D-bar difference reconstruction with regularized linear reconstruction in electrical impedance tomography. APPROACH: A standard regularized linear approach using a Laplacian penalty and the GREIT method for comparison to the D-bar difference images. Simulated data was generated using a circular phantom with small objects, as well as a 'Pac-Man' shaped conductivity target. An L-curve method was used for parameter selection in both D-bar and the regularized methods. MAIN RESULTS: We found that the D-bar method had a more position independent point spread function, was less sensitive to errors in electrode position and behaved differently with respect to additive noise than the regularized methods. SIGNIFICANCE: The results allow a novel pathway between traditional and D-bar algorithm comparison.
Authors: Andy Adler; Marcelo B Amato; John H Arnold; Richard Bayford; Marc Bodenstein; Stephan H Böhm; Brian H Brown; Inéz Frerichs; Ola Stenqvist; Norbert Weiler; Gerhard K Wolf Journal: Physiol Meas Date: 2012-04-24 Impact factor: 2.833
Authors: Andy Adler; John H Arnold; Richard Bayford; Andrea Borsic; Brian Brown; Paul Dixon; Theo J C Faes; Inéz Frerichs; Hervé Gagnon; Yvo Gärber; Bartłomiej Grychtol; Günter Hahn; William R B Lionheart; Anjum Malik; Robert P Patterson; Janet Stocks; Andrew Tizzard; Norbert Weiler; Gerhard K Wolf Journal: Physiol Meas Date: 2009-06-02 Impact factor: 2.833
Authors: S J Hamilton; D Isaacson; V Kolehmainen; P A Muller; J Toivanen; P F Bray Journal: Inverse Probl Imaging (Springfield) Date: 2021-05-01 Impact factor: 1.639