Single Molecule Microscopy meets Deep Learning

Single Molecule Microscopy meets Deep Learning

Author(s): Yoav Shechtman

Publication: Bunsen-Magazin 2024, 5, 115-117

Publisher: Deutsche Bunsen-Gesellschaft für physikalische Chemie e.V., Frankfurt

Language: English

DOI: 10.26125/yezz-vr28

Abstract: Recent advancements in the integration of Single Molecule Localization Microscopy (SMLM) with deep learning provided unprecedented capabilities in super-resolution microscopy and single particle tracking. Specifically, we discuss how it has improved the extension of SMLM to 3D imaging using Point Spread Function (PSF) engineering, e.g. by optimizing PSF designs with neural networks, and enabled super spatiotemporal resolved dynamics in live cells. In addition, we describe how the adoption of such methods is becoming simplified via accessible algorithms and 3D-printed phase masks.

Cite this:  Y. Shechtman, Bunsen-Magazin 2024, 5, 115-117, DOI: 10.26125/yezz-vr28

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