Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure th...

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Main Authors: Benjamin R Lavoie, Michal Okoniewski, Elise C Fear
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5017770?pdf=render
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author Benjamin R Lavoie
Michal Okoniewski
Elise C Fear
author_facet Benjamin R Lavoie
Michal Okoniewski
Elise C Fear
author_sort Benjamin R Lavoie
collection DOAJ
description We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.
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spelling doaj.art-1ed949a9b92243f6b4aa7062e69ace6c2022-12-22T03:00:32ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01119e016084910.1371/journal.pone.0160849Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.Benjamin R LavoieMichal OkoniewskiElise C FearWe present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.http://europepmc.org/articles/PMC5017770?pdf=render
spellingShingle Benjamin R Lavoie
Michal Okoniewski
Elise C Fear
Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
PLoS ONE
title Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
title_full Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
title_fullStr Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
title_full_unstemmed Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
title_short Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.
title_sort estimating the effective permittivity for reconstructing accurate microwave radar images
url http://europepmc.org/articles/PMC5017770?pdf=render
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