Deep learning-enhanced light-field imaging with continuous validation

Light field microscopy (LFM) has emerged as a powerful tool for fast volumetric image acquisition in biology, but its effective throughput and widespread use has been hampered by a computationally demanding and artefact-prone image reconstruction process. Here, we present a novel framework consisting of a hybrid light-field light-sheet microscope and deep learning-based volume reconstruction, where single light-sheet acquisitions continuously serve as training data and validation for the convolutional neural network reconstructing the LFM volume. Our network delivers high-quality reconstructions at video-rate throughput and we demonstrate the capabilities of our approach by imaging medaka heart dynamics and zebrafish neural activity.

Beuttenmueller, Fynn (author)
Norlin, NilsLund University,Lunds universitet,Molekylär neuromodulering,Forskargrupper vid Lunds universitet,Molecular Neuromodulation,Lund University Research Groups,European Molecular Biology Laboratory Heidelberg(Swepub:lu)ni5154no (author)
Gierten, Jakob (author)
Wittbrodt, Joachim (author)
Weigert, Martin (author)
Hufnagel, Lars (author)
Prevedel, Robert (author)
Kreshuk, AnnaEuropean Molecular Biology Laboratory Heidelberg (author)
European Molecular Biology Laboratory HeidelbergMolekylär neuromodulering (creator_code:org_t)

By the author/editor: Wagner, Nils; Beuttenmueller, ...; Norlin, Nils; Gierten, Jakob; Wittbrodt, Joach ...; Weigert, Martin; show more...; Hufnagel, Lars; Prevedel, Robert; Kreshuk, Anna; show less...

About the subject

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Basic Medicine; and Cell and Molecul ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.