Adaptive optics stochastic optical reconstruction microscopy (AO-STORM) by particle swarm optimization

Kayvan F Tehrani; Yiwen Zhang; Ping Shen; Peter Kner

doi:10.1364/BOE.8.005087

Adaptive optics stochastic optical reconstruction microscopy (AO-STORM) by particle swarm optimization

Biomed Opt Express. 2017 Oct 19;8(11):5087-5097. doi: 10.1364/BOE.8.005087. eCollection 2017 Nov 1.

Authors

Kayvan F Tehrani^{1

2}, Yiwen Zhang³, Ping Shen³, Peter Kner¹

Affiliations

¹ College of Engineering, University of Georgia, Athens, GA 30602, USA.
² Currently with the Regenerative Bioscience Center, University of Georgia, Athens, GA 30602, USA.
³ Department of Cellular Biology, University of Georgia, Athens, GA 30602, USA.

Abstract

Stochastic optical reconstruction microscopy (STORM) can achieve resolutions of better than 20nm imaging single fluorescently labeled cells. However, when optical aberrations induced by larger biological samples degrade the point spread function (PSF), the localization accuracy and number of localizations are both reduced, destroying the resolution of STORM. Adaptive optics (AO) can be used to correct the wavefront, restoring the high resolution of STORM. A challenge for AO-STORM microscopy is the development of robust optimization algorithms which can efficiently correct the wavefront from stochastic raw STORM images. Here we present the implementation of a particle swarm optimization (PSO) approach with a Fourier metric for real-time correction of wavefront aberrations during STORM acquisition. We apply our approach to imaging boutons 100 μm deep inside the central nervous system (CNS) of Drosophila melanogaster larvae achieving a resolution of 146 nm.

Keywords: (010.7350) Wave-front sensing; (100.3008) Image recognition, algorithms and filters; (110.7348) Aberration compensation; (180.2520) Fluorescence microscopy; (220.1080) Active or adaptive optics.