Deep learning-enhanced light-field imaging with continuous validation

Visualizing dynamic processes over large, three-dimensional fields of view at high speed is essential for many applications in the life sciences. Light-field microscopy (LFM) has emerged as a tool for fast volumetric image acquisition, but its effective throughput and widespread use in biology has been hampered by a computationally demanding and artifact-prone image reconstruction process. Here, we present a framework for artificial intelligence-enhanced microscopy, integrating a hybrid light-field light-sheet microscope and deep learning-based volume reconstruction. In our approach, concomitantly acquired, high-resolution two-dimensional light-sheet images continuously serve as training data and validation for the convolutional neural network reconstructing the raw LFM data during extended volumetric time-lapse imaging experiments. Our network delivers high-quality three-dimensional reconstructions at video-rate throughput, which can be further refined based on the high-resolution light-sheet images. We demonstrate the capabilities of our approach by imaging medaka heart dynamics and zebrafish neural activity with volumetric imaging rates up to 100 Hz.

Beuttenmueller, FynnHeidelberg University (author)
Norlin, NilsLund University,Lunds universitet,Molekylär neuromodulering,Forskargrupper vid Lunds universitet,Lund University Bioimaging Center,Medicinska fakulteten,Molecular Neuromodulation,Lund University Research Groups,Faculty of Medicine,European Molecular Biology Laboratory Heidelberg(Swepub:lu)ni5154no (author)
Gierten, JakobUniversity Hospital Heidelberg (author)
Boffi, Juan Carlos (author)
Wittbrodt, JoachimHeidelberg University (author)
Weigert, MartinSwiss Federal Institute of Technology (author)
Hufnagel, Lars (author)
Prevedel, RobertEuropean Molecular Biology Laboratory (EMBL Rome) (author)
Kreshuk, Anna (author)
European Molecular Biology Laboratory HeidelbergHeidelberg University (creator_code:org_t)

In:Nature Methods: Springer Science and Business Media LLC18:5, s. 557-5631548-71051548-7091

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

About the subject

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Radiology Nuclea ...

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