BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies

Abstract

Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.

BigNeuron: Large-Scale 3D Neuron Reconstruction from Optical Microscopy Images

“…Wang, 2011; Peng, et al, 2011, Polavaram et al, 2014, Wan et al, 2015, Santamaría-Pang, 2015). Some have vastly enhanced the competitive performance of tracing accuracy compared to the independent, manually curated reconstructions in public databases (Xiao, et al, 2013; Chiang, et al, 2011).…”

DeepNeuron: An Open Deep Learning Toolbox for Neuron Tracing

“…Using the trained models, we filtered out falsely detected signals and pruned the reconstructed neuronal tree. Furthermore, different tracing results generated from multiple base tracing algorithms could be combined (Wan, et al, 2015) to produce a consensus using this module ( Figure 6).…”

Reconstructing the brain: from image stacks to neuron synthesis

“…Vaa3D comes with a set of morphometric features that are consistent with the popular neuron morphometric analysis tool L-measure [6]. Vaa3D also provides neuron search and comparison tools such as BlastNeuron [7]. …”