DOAJ Open Access 2022

GANscan: continuous scanning microscopy using deep learning deblurring

Michael John Fanous Gabriel Popescu

Abstrak

In order to speed up the microscopy acquisition process, we developed a method, termed GANscan, in which videos are recorded as the stage is moving at high speeds. Using generative adversarial networks (GANs), we achieve 30x the throughput of stop-and-stare systems.

Topik & Kata Kunci

Applied optics. Photonics Optics. Light

Penulis (2)

Michael John Fanous

Gabriel Popescu

Format Sitasi

APA MLA BibTeX

Fanous, M.J., Popescu, G. (2022). GANscan: continuous scanning microscopy using deep learning deblurring. https://doi.org/10.1038/s41377-022-00952-z

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Informasi Jurnal

Tahun Terbit: 2022
Sumber Database: DOAJ
DOI: 10.1038/s41377-022-00952-z
Akses: Open Access ✓