4.6 Article

Sensorless Wavefront Correction in Two-Photon Microscopy Across Different Turbidity Scales

Journal

FRONTIERS IN PHYSICS
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fphy.2022.884053

Keywords

multiphoton microscopy; adaptive optics; scatter compensation; wavefront sensing; brain imaging; aberration and wavefront analysis

Ask authors/readers for more resources

Adaptive optics (AO) is a powerful tool for increasing the imaging depth of multiphoton scanning microscopes. Dynamic Adaptive Scattering compensation Holography (DASH) is a fast-converging sensorless AO technique used for scatter compensation. This study investigates the performance of DASH under different turbidity conditions.
Adaptive optics (AO) is a powerful tool to increase the imaging depth of multiphoton scanning microscopes. For highly scattering tissues, sensorless wavefront correction techniques exhibit robust performance and present a straight-forward implementation of AO. However, for many applications such as live-tissue imaging, the speed of aberration correction remains a critical bottleneck. Dynamic Adaptive Scattering compensation Holography (DASH)-a fast-converging sensorless AO technique introduced recently for scatter compensation in nonlinear scanning microscopy-addresses this issue. DASH has been targeted at highly turbid media, but to-date it has remained an open question how it performs for mild turbidity, where limitations imposed by phase-only wavefront shaping are expected to impede its convergence. In this work, we study the performance of DASH across different turbidity regimes, in simulation as well as experiments. We further provide a direct comparison between DASH and a novel, modified version of the Continuous Sequential Algorithm (CSA) which we call Amplified CSA (a-CSA).

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available