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Closed-loop wavefront sensing and correction in the mouse brain with computed optical coherence microscopy.

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Biomedical Optics Express
|September 13, 2021
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Summary
This summary is machine-generated.

Computational adaptive optics (CAO) using optical coherence microscopy (OCM) effectively corrects low-order aberrations in mouse brain tissue. This method improves OCM signal intensity by 3× at depths of nearly 1 mm.

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Area of Science:

  • Biomedical Optics
  • Adaptive Optics
  • Optical Coherence Microscopy

Background:

  • Optical coherence microscopy (OCM) offers high-sensitivity imaging by capturing complex optical fields.
  • Computational wavefront retrieval using back-scattered light is enabled by OCM's sensitivity.
  • Computational adaptive optics (CAO) in OCM leverages coherence and confocal gating for aberration sensing.

Purpose of the Study:

  • To investigate the performance of CAO-based aberration sensing in OCM.
  • To evaluate CAO performance in simulations, phantoms, and ex vivo mouse brain tissue.
  • To assess the effectiveness of correcting tissue-induced aberrations using CAO in OCM.

Main Methods:

  • Performed simulations, used bead phantoms, and imaged ex vivo mouse brain tissue.
  • Employed computational adaptive optics (CAO) for aberration sensing within OCM.
  • Focused on sensing and correcting low-order aberrations (astigmatism, coma, trefoil).

Main Results:

  • CAO-based aberration sensing in OCM can face signal attenuation and shape similarity issues for high-order aberrations due to imaging geometry.
  • Correction of low-order aberrations successfully mitigated tissue-induced aberrations in ex vivo mouse brain.
  • Achieved a 3× increase in OCM signal intensity at a depth of approximately 0.9 mm.

Conclusions:

  • Sensing and correcting low-order aberrations with CAO in OCM is effective for biological tissues.
  • This approach significantly enhances imaging depth and signal quality in OCM of mouse brain.
  • CAO offers a viable strategy for improving OCM performance in scattering biological samples.