Pipeline for the Creation of Surface-based Averaged Brain Atlases

Abstract

Digital atlases of the brain serve as a spatial reference frame which can be used to relate data from different image modalities and experiments. In this paper we describe a standardized pipeline for the creation of extendable surface-based anatomical insect brain atlases from 3D image data of a population of individuals. The pipeline consists of the major steps imaging and preprocessing, segmentation, averaging, surface reconstruction, and surface simplification. At first, 3D image data sets from confocal microscopy are resized, stitched, and initially displayed using standard image processing and visualization tools. Then brain structures, such as neuropils and neurons, are labeled by means of manual segmentation and line extraction algorithms. The averaging step comprises affine and elastic registration and a mean shape selection strategy. Finally non-manifold surfaces of the labeled and aligned structures are reconstructed using a generalized surface reconstruction algorithm. These surfaces are simplified and adapted to further needs by decimation and retriangulation. The chosen methods of each step are adequate for a variety of data. We propose an iterative application of the pipeline in order to build the atlas in a hierarchical fashion, integrating successively more levels of detail. The approach is applied in several different neurobiological research fields.