We address the problem of building three-dimensional connectivity maps for neurons from sectional electron microscopy. Sectional data consists of a stack of very high-resolution, two-dimensional images that are oriented to capture cross sections of elongated neuronal processes. High magnification serial microscopy images have the potential to expand the field of neurophysiological modeling by providing ground-truth neuroanatomical data. However, their complexity and vast size make them impractical for human interpretation. This project aims at building automatic and semi-automatic tools to assist researchers in analyzing such data.