A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy

John P. Dumas, Muhammad A. Lodhi, Batoul A. Taki, Waheed Uz Zaman Bajwa, Mark Pierce

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Confocal, multi-photon, and wide-field endomicroscopy often use coherent fiber-optic bundles to facilitate in vivo imaging. The narrow diameter and flexibility of these bundles allow excellent tissue access, but fabrication processes place a practical limit on fiber packing density, restricting the number of resolvable points in an image. Furthermore, the hexagonal packing of discrete fibers creates inter-fiber gaps that prevent some regions of the object from being imaged. We have combined compressed sensing (CS) principles with dispersive optics to simultaneously address these two fundamental limitations of the fiber bundle architecture. We previously reported a CS approach to improve the spatial resolution of bundle based imaging systems by recovering multiple resolvable points within each fiber (Dumas et al., Proc. SPIE 2018). This manuscript will discuss and integrate approaches for recovering object details that lie behind inter-fiber gaps with our CS-based method for resolving intra-fiber detail. First, we show that modifying our CS model to consider the whole field of view rather than a discrete point for each fiber can partially recover inter-fiber detail. Next, we outline how a dispersive component at the distal end of the bundle can be used to spectrally shift object detail such that information from all locations on the sample are transmitted through the bundle. We then implement image compounding techniques with our CS approach to produce a more continuous image. We demonstrate that our platform can produce images of biological samples with 65,536 resolved pixels using a fiber bundle with only 3,700 fiber cores.

Original languageEnglish (US)
Title of host publicationEndoscopic Microscopy XIV
EditorsGuillermo J. Tearney, Thomas D. Wang, Melissa J. Suter
PublisherSPIE
ISBN (Electronic)9781510623507
DOIs
StatePublished - Jan 1 2019
EventEndoscopic Microscopy XIV 2019 - San Francisco, United States
Duration: Feb 2 2019Feb 4 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10854
ISSN (Print)1605-7422

Conference

ConferenceEndoscopic Microscopy XIV 2019
CountryUnited States
CitySan Francisco
Period2/2/192/4/19

Fingerprint

Photons
bundles
Imaging techniques
fibers
Fibers
augmentation
Compressed sensing
compounding
packing density
Imaging systems
Fiber optics
field of view
fiber optics
Optics
flexibility
platforms
spatial resolution
Pixels
pixels
optics

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Keywords

  • compressed sensing
  • Compressive imaging
  • endomicroscopy
  • fiber bundle
  • snapshot spectral coding

Cite this

Dumas, J. P., Lodhi, M. A., Taki, B. A., Bajwa, W. U. Z., & Pierce, M. (2019). A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy. In G. J. Tearney, T. D. Wang, & M. J. Suter (Eds.), Endoscopic Microscopy XIV [1085416] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10854). SPIE. https://doi.org/10.1117/12.2509053
Dumas, John P. ; Lodhi, Muhammad A. ; Taki, Batoul A. ; Bajwa, Waheed Uz Zaman ; Pierce, Mark. / A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy. Endoscopic Microscopy XIV. editor / Guillermo J. Tearney ; Thomas D. Wang ; Melissa J. Suter. SPIE, 2019. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).
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Dumas, JP, Lodhi, MA, Taki, BA, Bajwa, WUZ & Pierce, M 2019, A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy. in GJ Tearney, TD Wang & MJ Suter (eds), Endoscopic Microscopy XIV., 1085416, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10854, SPIE, Endoscopic Microscopy XIV 2019, San Francisco, United States, 2/2/19. https://doi.org/10.1117/12.2509053

A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy. / Dumas, John P.; Lodhi, Muhammad A.; Taki, Batoul A.; Bajwa, Waheed Uz Zaman; Pierce, Mark.

Endoscopic Microscopy XIV. ed. / Guillermo J. Tearney; Thomas D. Wang; Melissa J. Suter. SPIE, 2019. 1085416 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10854).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Confocal, multi-photon, and wide-field endomicroscopy often use coherent fiber-optic bundles to facilitate in vivo imaging. The narrow diameter and flexibility of these bundles allow excellent tissue access, but fabrication processes place a practical limit on fiber packing density, restricting the number of resolvable points in an image. Furthermore, the hexagonal packing of discrete fibers creates inter-fiber gaps that prevent some regions of the object from being imaged. We have combined compressed sensing (CS) principles with dispersive optics to simultaneously address these two fundamental limitations of the fiber bundle architecture. We previously reported a CS approach to improve the spatial resolution of bundle based imaging systems by recovering multiple resolvable points within each fiber (Dumas et al., Proc. SPIE 2018). This manuscript will discuss and integrate approaches for recovering object details that lie behind inter-fiber gaps with our CS-based method for resolving intra-fiber detail. First, we show that modifying our CS model to consider the whole field of view rather than a discrete point for each fiber can partially recover inter-fiber detail. Next, we outline how a dispersive component at the distal end of the bundle can be used to spectrally shift object detail such that information from all locations on the sample are transmitted through the bundle. We then implement image compounding techniques with our CS approach to produce a more continuous image. We demonstrate that our platform can produce images of biological samples with 65,536 resolved pixels using a fiber bundle with only 3,700 fiber cores.

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Dumas JP, Lodhi MA, Taki BA, Bajwa WUZ, Pierce M. A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy. In Tearney GJ, Wang TD, Suter MJ, editors, Endoscopic Microscopy XIV. SPIE. 2019. 1085416. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). https://doi.org/10.1117/12.2509053