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Computational optical imaging with a photonic lantern.

Debaditya Choudhury1,2, Duncan K McNicholl1,2, Audrey Repetti3,4

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Summary
This summary is machine-generated.

High-resolution in-vivo imaging is achieved using a multicore fiber (MCF) and a photonic lantern. This novel approach enables single-pixel imaging for enhanced biological process visualization.

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Area of Science:

  • Biomedical Optics
  • Optical Engineering
  • Computational Imaging

Background:

  • Optical fibers are ideal for in-vivo biological imaging due to their flexibility.
  • Current microendoscopic techniques face limitations in achieving high spatial resolution.
  • Need for advanced imaging modalities to overcome resolution barriers in biological studies.

Purpose of the Study:

  • To develop a high-resolution microendoscopy technique using multicore fibers (MCF).
  • To demonstrate a novel single-pixel imaging approach for in-vivo biological visualization.
  • To introduce a computational imaging algorithm for reconstructing images from MCF-based data.

Main Methods:

  • Utilized a multicore fiber (MCF) with a tapered photonic lantern transition at the distal end.
  • Individually excited single-mode MCF cores to project distinct, stable multimode light patterns.
  • Employed a single-pixel detector to measure transmitted light fractions for each pattern.
  • Developed and applied the SARA-COIL computational imaging algorithm for image reconstruction.

Main Results:

  • Demonstrated stable projection of distinct multimode light patterns from the photonic lantern.
  • Successfully implemented single-pixel imaging by measuring transmitted light through an object.
  • Reconstructed object images using the SARA-COIL algorithm and pre-measured light patterns.
  • Achieved high-resolution microendoscopy, overcoming limitations of current methods.

Conclusions:

  • The developed MCF-based photonic lantern system offers a route to high-resolution microendoscopy.
  • Single-pixel imaging combined with computational reconstruction provides a viable method for in-vivo biological imaging.
  • This technology has the potential to significantly advance the visualization of biological processes.