Open AccessAutomated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive optics
Author(s) -
Rishyashring R. Iyer,
Yuan Zhi Liu,
Stephen A. Boppart
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.012998
Subject(s) - adaptive optics , deformable mirror , optics , wavefront , computer science , interferometry , wavefront sensor , performance metric , focus (optics) , metric (unit) , image quality , computational complexity theory , computer vision , artificial intelligence , physics , algorithm , image (mathematics) , management , economics , operations management
Traditional wavefront-sensor-based adaptive optics (AO) techniques face numerous challenges that cause poor performance in scattering samples. Sensorless closed-loop AO techniques overcome these challenges by optimizing an image metric at different states of a deformable mirror (DM). This requires acquisition of a series of images continuously for optimization - an arduous task in dynamic in vivo samples. We present a technique where the different states of the DM are instead simulated using computational adaptive optics (CAO). The optimal wavefront is estimated by performing CAO on an initial volume to minimize an image metric, and then the pattern is translated to the DM. In this paper, we have demonstrated this technique on a spectral-domain optical coherence microscope for three applications: real-time depth-wise aberration correction, single-shot volumetric aberration correction, and extension of depth-of-focus. Our technique overcomes the disadvantages of sensor-based AO, reduces the number of image acquisitions compared to traditional sensorless AO, and retains the advantages of both computational and hardware-based AO.