Paper
7 December 2021 Robust optical autofocus system utilizing neural networks applied to automated multiwell plate STORM microscopy
J. Lightley, F. Görlitz, S. Kumar, R. Kalita, A. Kolbeinsson, E. Garcia, Y. Alexandrov, V. Bousgouni, R. Wysoczanski, P. Barnes, L.. Donelly, C. Bakal, C. Dunsby, M. A. A. Neil, S. Flaxman, P. M. W. French
Author Affiliations +
Abstract
We present a robust, low-cost neural network-based optical autofocus system that can operate over a range of ±100μm with submicron precision, enabling automated high-content super-resolved imaging with a 1.3 NA objective lens.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Lightley, F. Görlitz, S. Kumar, R. Kalita, A. Kolbeinsson, E. Garcia, Y. Alexandrov, V. Bousgouni, R. Wysoczanski, P. Barnes, L.. Donelly, C. Bakal, C. Dunsby, M. A. A. Neil, S. Flaxman, and P. M. W. French "Robust optical autofocus system utilizing neural networks applied to automated multiwell plate STORM microscopy", Proc. SPIE 11922, Advances in Microscopic Imaging III, 1192205 (7 December 2021); https://doi.org/10.1117/12.2615663
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KEYWORDS
Data acquisition

Microscopes

Data modeling

Microscopy

Imaging systems

Neural networks

Objectives

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