TY - JOUR T1 - Automated Reconstruction of a Serial-Section EM <em>Drosophila</em> Brain with Flood-Filling Networks and Local Realignment JF - bioRxiv DO - 10.1101/605634 SP - 605634 AU - Peter H. Li AU - Larry F. Lindsey AU - Michał Januszewski AU - Zhihao Zheng AU - Alexander Shakeel Bates AU - István Taisz AU - Mike Tyka AU - Matthew Nichols AU - Feng Li AU - Eric Perlman AU - Jeremy Maitin-Shepard AU - Tim Blakely AU - Laramie Leavitt AU - Gregory S.X.E. Jefferis AU - Davi Bock AU - Viren Jain Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/08/04/605634.abstract N2 - 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 as well as dynamically adjust and synthesize 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. ER -