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Serial section electron microscopy (ssEM) is a widely used technique forobtaining volumetric information of biological tissues at nanometer scale.However, accurate 3D reconstructions of identified cellular structures andvolumetric quantifications require precise estimates of section thickness andanisotropy (or stretching) along the XY imaging plane. In fact, many imageprocessing algorithms simply assume isotropy within the imaging plane. Toameliorate this problem, we present a method for estimating thickness andstretching of electron microscopy sections using non-parametric Bayesianregression of image statistics. We verify our thickness and stretchingestimates using direct measurements obtained by atomic force microscopy (AFM)and show that our method has a lower estimation error compared to a recentindirect thickness estimation method as well as a relative Z coordinateestimation method. Furthermore, we have made the first dataset of ssSEM imageswith directly measured section thickness values publicly available for theevaluation of indirect thickness estimation methods.

Estimation of Z-Thickness and XY-Anisotropy of Electron Microscopy Images using Gaussian Processes