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Deconvolution for multimode fiber imaging: modeling of spatially variant PSF

Focusing light through a step-index multimode optical fiber (MMF) using wavefront control enables minimally-invasive endoscopy of biological tissue. The point spread function (PSF) of such an imaging system is spatially variant, and this variation limits compensation for blurring using most deconvol...

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Autores principales: Turcotte, Raphaël, Sutu, Eusebiu, Schmidt, Carla C., Emptage, Nigel J., Booth, Martin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Optical Society of America 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449755/
https://www.ncbi.nlm.nih.gov/pubmed/32923076
http://dx.doi.org/10.1364/BOE.399983
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author Turcotte, Raphaël
Sutu, Eusebiu
Schmidt, Carla C.
Emptage, Nigel J.
Booth, Martin J.
author_facet Turcotte, Raphaël
Sutu, Eusebiu
Schmidt, Carla C.
Emptage, Nigel J.
Booth, Martin J.
author_sort Turcotte, Raphaël
collection PubMed
description Focusing light through a step-index multimode optical fiber (MMF) using wavefront control enables minimally-invasive endoscopy of biological tissue. The point spread function (PSF) of such an imaging system is spatially variant, and this variation limits compensation for blurring using most deconvolution algorithms as they require a uniform PSF. However, modeling the spatially variant PSF into a series of spatially invariant PSFs re-opens the possibility of deconvolution. To achieve this we developed svmPSF: an open-source Java-based framework compatible with ImageJ. The approach takes a series of point response measurements across the field-of-view (FOV) and applies principal component analysis to the measurements' co-variance matrix to generate a PSF model. By combining the svmPSF output with a modified Richardson-Lucy deconvolution algorithm, we were able to deblur and regularize fluorescence images of beads and live neurons acquired with a MMF, and thus effectively increasing the FOV.
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spelling pubmed-74497552020-09-11 Deconvolution for multimode fiber imaging: modeling of spatially variant PSF Turcotte, Raphaël Sutu, Eusebiu Schmidt, Carla C. Emptage, Nigel J. Booth, Martin J. Biomed Opt Express Article Focusing light through a step-index multimode optical fiber (MMF) using wavefront control enables minimally-invasive endoscopy of biological tissue. The point spread function (PSF) of such an imaging system is spatially variant, and this variation limits compensation for blurring using most deconvolution algorithms as they require a uniform PSF. However, modeling the spatially variant PSF into a series of spatially invariant PSFs re-opens the possibility of deconvolution. To achieve this we developed svmPSF: an open-source Java-based framework compatible with ImageJ. The approach takes a series of point response measurements across the field-of-view (FOV) and applies principal component analysis to the measurements' co-variance matrix to generate a PSF model. By combining the svmPSF output with a modified Richardson-Lucy deconvolution algorithm, we were able to deblur and regularize fluorescence images of beads and live neurons acquired with a MMF, and thus effectively increasing the FOV. Optical Society of America 2020-07-29 /pmc/articles/PMC7449755/ /pubmed/32923076 http://dx.doi.org/10.1364/BOE.399983 Text en Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) . Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
spellingShingle Article
Turcotte, Raphaël
Sutu, Eusebiu
Schmidt, Carla C.
Emptage, Nigel J.
Booth, Martin J.
Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title_full Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title_fullStr Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title_full_unstemmed Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title_short Deconvolution for multimode fiber imaging: modeling of spatially variant PSF
title_sort deconvolution for multimode fiber imaging: modeling of spatially variant psf
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449755/
https://www.ncbi.nlm.nih.gov/pubmed/32923076
http://dx.doi.org/10.1364/BOE.399983
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