ArticleNeuroinformatics2015
BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies.
Article in Neuroinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Connectivity of single neurons classifies cell subtypes in mouse brains.Nature methods · 2025Article
- Neuronal diversity and stereotypy at multiple scales through whole brain morphometry.Nature communications · 2024Article
- DSM: Deep sequential model for complete neuronal morphology representation and feature extraction.Patterns (New York, N.Y.) · 2024Article
- Multi-gate Weighted Fusion Network for neuronal morphology classification.Frontiers in neuroscience · 2024Article
- Multi-level feature fusion network for neuronal morphology classification.Frontiers in neuroscience · 2024Article
- Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy.Science advances · 2023Article
- A robust approach to 3D neuron shape representation for quantification and classification.BMC bioinformatics · 2023Article
- Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.Research square · 2023Article
- CAJAL enables analysis and integration of single-cell morphological data using metric geometry.Nature communications · 2023Article
- Neuronal Connectivity as a Determinant of Cell Types and Subtypes.Research square · 2023Article
- Large scale similarity search across digital reconstructions of neural morphology.Neuroscience research · 2022Article
- Smart imaging to empower brain-wide neuroscience at single-cell levels.Brain informatics · 2022Review
- Efficient metadata mining of web-accessible neural morphologies.Progress in biophysics and molecular biology · 2022Article
- Exploring highly reliable substructures in auto-reconstructions of a neuron.Brain informatics · 2021Article
- Article
- Retrieving similar substructures on 3D neuron reconstructions.Brain informatics · 2020Article
- Axonal Tree Morphology and Signal Propagation Dynamics Improve Interneuron Classification.Neuroinformatics · 2020Article
- NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity.Neuroinformatics · 2020Article
- Article
- Cocaine-Induced Preference Conditioning: a Machine Vision Perspective.Neuroinformatics · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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.
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