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Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment

View ORCID ProfilePeter H. Li, Larry F. Lindsey, View ORCID ProfileMichał Januszewski, Zhihao Zheng, Alexander Shakeel Bates, István Taisz, Mike Tyka, Matthew Nichols, Feng Li, Eric Perlman, Jeremy Maitin-Shepard, Tim Blakely, Laramie Leavitt, Gregory S.X.E. Jefferis, Davi Bock, View ORCID ProfileViren Jain
doi: https://doi.org/10.1101/605634
Peter H. Li
Google AI, Mountain View, CA, USA
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  • For correspondence: phli@google.com
Larry F. Lindsey
Google AI, Mountain View, CA, USA
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Michał Januszewski
Google AI, Mountain View, CA, USA
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Zhihao Zheng
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
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Alexander Shakeel Bates
Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
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István Taisz
Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
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Mike Tyka
Google AI, Mountain View, CA, USA
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Matthew Nichols
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
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Feng Li
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
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Eric Perlman
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
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Jeremy Maitin-Shepard
Google AI, Mountain View, CA, USA
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Tim Blakely
Google AI, Mountain View, CA, USA
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Laramie Leavitt
Google AI, Mountain View, CA, USA
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Gregory S.X.E. Jefferis
Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UKDepartment of Zoology, University of Cambridge, Cambridge, UK
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Davi Bock
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USADepartment of Neurological Sciences, University of Vermont, Burlington, VT, USA
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Viren Jain
Google AI, Mountain View, CA, USA
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  • ORCID record for Viren Jain
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Abstract

Reconstruction of neural circuitry at single-synapse resolution is an attractive target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs were combined with procedures that locally re-align serial sections and dynamically adjust image content. The proposed approach produced a largely merger-free segmentation of the entire ssTEM Drosophila brain, which we make freely available. As compared to manual tracing using an efficient skeletonization strategy, the segmentation enabled circuit reconstruction and analysis workflows that were an order of magnitude faster.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 11, 2019.
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Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment
Peter H. Li, Larry F. Lindsey, Michał Januszewski, Zhihao Zheng, Alexander Shakeel Bates, István Taisz, Mike Tyka, Matthew Nichols, Feng Li, Eric Perlman, Jeremy Maitin-Shepard, Tim Blakely, Laramie Leavitt, Gregory S.X.E. Jefferis, Davi Bock, Viren Jain
bioRxiv 605634; doi: https://doi.org/10.1101/605634
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Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment
Peter H. Li, Larry F. Lindsey, Michał Januszewski, Zhihao Zheng, Alexander Shakeel Bates, István Taisz, Mike Tyka, Matthew Nichols, Feng Li, Eric Perlman, Jeremy Maitin-Shepard, Tim Blakely, Laramie Leavitt, Gregory S.X.E. Jefferis, Davi Bock, Viren Jain
bioRxiv 605634; doi: https://doi.org/10.1101/605634

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