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Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model

We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with...

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Detalles Bibliográficos
Autores principales: Troiani, Francesca, Nikolic, Konstantin, Constandinou, Timothy G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039043/
https://www.ncbi.nlm.nih.gov/pubmed/29990346
http://dx.doi.org/10.1371/journal.pone.0200392
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author Troiani, Francesca
Nikolic, Konstantin
Constandinou, Timothy G.
author_facet Troiani, Francesca
Nikolic, Konstantin
Constandinou, Timothy G.
author_sort Troiani, Francesca
collection PubMed
description We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with external software. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work aims to understand to what extent time domain OCT can be used for non-invasive, direct optical monitoring of peripheral nerve activity.
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spelling pubmed-60390432018-07-19 Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model Troiani, Francesca Nikolic, Konstantin Constandinou, Timothy G. PLoS One Research Article We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with external software. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work aims to understand to what extent time domain OCT can be used for non-invasive, direct optical monitoring of peripheral nerve activity. Public Library of Science 2018-07-10 /pmc/articles/PMC6039043/ /pubmed/29990346 http://dx.doi.org/10.1371/journal.pone.0200392 Text en © 2018 Troiani et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Troiani, Francesca
Nikolic, Konstantin
Constandinou, Timothy G.
Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title_full Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title_fullStr Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title_full_unstemmed Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title_short Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model
title_sort simulating optical coherence tomography for observing nerve activity: a finite difference time domain bi-dimensional model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039043/
https://www.ncbi.nlm.nih.gov/pubmed/29990346
http://dx.doi.org/10.1371/journal.pone.0200392
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