Three-dimensional reconstruction of neuronal forests

Three-dimensional reconstruction of neuronal forests from a coherent volumetric data set representing Golgi-stained cortical material is demonstrated. The system automates in parallel neuron feature extraction and reconstruction, replacing largely manual techniques for tracing individual neurons. Serial sections were digitized at 1024 x 1024 pixels at a linear resolution of 0.37 mum, and then digitally aligned into a coherent volume data set. Our reconstruction program, Recon, determined regions of interest (ROIs) in each image and culled data aggressively, reducing the original volumetric data 70-fold into an ROI-based aligned image stack. The neuronal forest of Fig. 1 below was treaded from this reduced data set. (C) 2001 Published by Elsevier Science B.V.