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Motivation: Serial section microscopy is an established method for detailedanatomy reconstruction of biological specimen. During the last decade, highresolution electron microscopy (EM) of serial sections has become the de-factostandard for reconstruction of neural connectivity at ever increasing scales(EM connectomics). In serial section microscopy, the axial dimension of thevolume is sampled by physically removing thin sections from the embeddedspecimen and subsequently imaging either the block-face or the section series.This process has limited precision leading to inhomogeneous non-planar samplingof the axial dimension of the volume which, in turn, results in distorted imagevolumes. This includes that section series may be collected and imaged inunknown order.  Results: We developed methods to identify and correct these distortionsthrough image-based signal analysis without any additional physical apparatusor measurements. We demonstrate the efficacy of our methods in proof ofprinciple experiments and application to real world problems.  Availability and Implementation: We made our work available as libraries forthe ImageJ distribution Fiji and for deployment in a high performance parallelcomputing environment. Our sources are open and available athttp://github.com/saalfeldla/section-sort,http://github.com/saalfeldlab/em-thickness-estimation, andhttp://github.com/saalfeldlab/z-spacing-spark.  Contact: saalfelds@janelia.hhmi.org

Image-Based Correction of Continuous and Discontinuous Non-Planar Axial Distortion in Serial Section Microscopy