A Fuzzy Algorithm to Trace Stained Neurons in Serial Block-Face Scanning Electron Microscopy Image Series

Abstract

With the recently developed serial block-face scanning electron microscope (SBFSEM) it is now possible to analyze the 3-D structure of biological specimens at a resolution that is one order of magnitude better compared to light microscopy requiring minimal user input. It allows the automatic creation of large series (≫ 1000) of digitally imaged ultra-thin sections (≪ 100 nm) from heavy metal-stained and plastic embedded tissue. Together with the ability of selectively staining individual, identified neurons using electron dense material one can visually track the complete structure at a resolution as low as 20x20x40 nm. Here we introduce a simple fuzzy region-growing tracing algorithm that incorporates a minimum of prior knowledge about object and background gray level distributions. We show that this algorithm reliably traces structures of interest over several hundreds of sections opening the unique opportunity to systematically study the morphology of neuronal structures at the nanometre scale in a fully automated way.