TY - UNPB
T1 - Deep learning-enhanced light-field imaging with continuous validation
AU - Wagner, Nils
AU - Beuttenmueller, Fynn
AU - Norlin, Nils
AU - Gierten, Jakob
AU - Wittbrodt, Joachim
AU - Weigert, Martin
AU - Hufnagel, Lars
AU - Prevedel, Robert
AU - Kreshuk, Anna
PY - 2020/7/31
Y1 - 2020/7/31
N2 - 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.
AB - 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.
UR - http://biorxiv.org/content/early/2020/07/31/2020.07.30.228924.abstract
U2 - 10.1101/2020.07.30.228924
DO - 10.1101/2020.07.30.228924
M3 - Preprint (in preprint archive)
T3 - bioRxiv
BT - Deep learning-enhanced light-field imaging with continuous validation
PB - bioRxiv
ER -