  The most established method of reconstructing neural circuits from animals
involves slicing tissue very thin, then taking mosaics of electron microscope
(EM) images. To trace neurons across different images and through different
sections, these images must be accurately aligned, both with the others in the
same section and to the sections above and below. Unfortunately, sectioning and
imaging are not ideal processes - some of the problems that make alignment
difficult include lens distortion, tissue shrinkage during imaging, tears and
folds in the sectioned tissue, and dust and other artifacts. In addition the
data sets are large (hundreds of thousands of images) and each image must be
aligned with many neighbors, so the process must be automated and reliable.
This paper discusses methods of dealing with these problems, with numeric
results describing the accuracy of the resulting alignments.
