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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Optical Society of America
2020
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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. |
format | Online Article Text |
id | pubmed-7449755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Optical Society of America |
record_format | MEDLINE/PubMed |
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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