Deconvolution for multimode fiber imaging: Open-source 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...
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Journal article |
| Kieli: | English |
| Julkaistu: |
Optical Society of America
2020
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| _version_ | 1826264313183076352 |
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| author | Turcotte, R Sutu, E Schmidt, C Emptage, N Booth, M |
| author_facet | Turcotte, R Sutu, E Schmidt, C Emptage, N Booth, M |
| author_sort | Turcotte, R |
| collection | OXFORD |
| 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. |
| first_indexed | 2024-03-06T20:05:47Z |
| format | Journal article |
| id | oxford-uuid:28dcdebe-fabf-416b-a9d7-df04696ae20a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:05:47Z |
| publishDate | 2020 |
| publisher | Optical Society of America |
| record_format | dspace |
| spelling | oxford-uuid:28dcdebe-fabf-416b-a9d7-df04696ae20a2022-03-26T12:15:33ZDeconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSFJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:28dcdebe-fabf-416b-a9d7-df04696ae20aEnglishSymplectic ElementsOptical Society of America2020Turcotte, RSutu, ESchmidt, CEmptage, NBooth, MFocusing 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. |
| spellingShingle | Turcotte, R Sutu, E Schmidt, C Emptage, N Booth, M Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title | Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title_full | Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title_fullStr | Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title_full_unstemmed | Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title_short | Deconvolution for multimode fiber imaging: Open-source modeling of spatially variant PSF |
| title_sort | deconvolution for multimode fiber imaging open source modeling of spatially variant psf |
| work_keys_str_mv | AT turcotter deconvolutionformultimodefiberimagingopensourcemodelingofspatiallyvariantpsf AT sutue deconvolutionformultimodefiberimagingopensourcemodelingofspatiallyvariantpsf AT schmidtc deconvolutionformultimodefiberimagingopensourcemodelingofspatiallyvariantpsf AT emptagen deconvolutionformultimodefiberimagingopensourcemodelingofspatiallyvariantpsf AT boothm deconvolutionformultimodefiberimagingopensourcemodelingofspatiallyvariantpsf |