Universal adaptive optics for microscopy through embedded neural network control.

ABSTRACT: The resolution and contrast of microscope imaging is often affected by aberrations introduced by imperfect optical systems and inhomogeneous refractive structures in specimens. Adaptive optics (AO) compensates these aberrations and restores diffraction limited performance. A wide range of AO solutions have been introduced, often tailored to a specific microscope type or application. Until now, a universal AO solution - one that can be readily transferred between microscope modalities - has not been deployed. We propose versatile and fast aberration correction using a physics-based machine learning assisted wavefront-sensorless AO control (MLAO) method. Unlike previous ML methods, we used a specially constructed neural network (NN) architecture, designed using physical understanding of the

SUBMITTER: Hu Q 

PROVIDER: S-EPMC10641083 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature