  We present an updated version of the VESICLE-CNN algorithm presented by
Roncal et al. (2014). The original implementation makes use of a patch-based
approach. This methodology is known to be slow due to repeated computations. We
update this implementation to be fully convolutional through the use of dilated
convolutions, recovering the expanded field of view achieved through the use of
strided maxpools, but without a degradation of spatial resolution. This updated
implementation performs as well as the original implementation, but with a
$600\times$ speedup at test time. We release source code and data into the
public domain.
