TY - JOUR T1 - High-Precision Automated Reconstruction of Neurons with Flood-filling Networks JF - bioRxiv DO - 10.1101/200675 SP - 200675 AU - Michał Januszewski AU - Jörgen Kornfeld AU - Peter H. Li AU - Art Pope AU - Tim Blakely AU - Larry Lindsey AU - Jeremy Maitin-Shepard AU - Mike Tyka AU - Winfried Denk AU - Viren Jain Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/10/09/200675.abstract N2 - Reconstruction of neural circuits from volume electron microscopy data requires the tracing of complete cells including all their neurites. Automated approaches have been developed to perform the tracing, but without costly human proofreading their error rates are too high to obtain reliable circuit diagrams. We present a method for automated segmentation that, like the majority of previous efforts, employs convolutional neural networks, but contains in addition a recurrent pathway that allows the iterative optimization and extension of the reconstructed shape of individual neural processes. We used this technique, which we call flood-filling networks, to trace neurons in a data set obtained by serial block-face electron microscopy from a male zebra finch brain. Our method achieved a mean error-free neurite path length of 1.1 mm, an order of magnitude better than previously published approaches applied to the same dataset. Only 4 mergers were observed in a neurite test set of 97 mm path length. ER -