ArticleScientific reports2023
SpineTool is an open-source software for analysis of morphology of dendritic spines.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- Deep learning-assisted mapping of dendritic spines using sequential 2D two-photon calcium imaging.iScience · 2026Article
- Curvature-based machine-learning method for automated segmentation of dendritic spines.Biophysical journal · 2026Article
- 3D dendritic spines shape descriptors for efficient classification and morphology analysis in control and Alzheimer's disease modeling neurons.Bioinformatics (Oxford, England) · 2026Article
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- Article
- CURVATURE-BASED MACHINE LEARNING METHOD FOR AUTOMATED SEGMENTATION OF DENDRITIC SPINES.bioRxiv : the preprint server for biology · 2025Article
- A deep learning pipeline for accurate and automated restoration, segmentation, and quantification of dendritic spines.Cell reports methods · 2025Article
- NeuroDecon: A Neural Network-Based Method for Three-Dimensional Deconvolution of Fluorescent Microscopic Images.International journal of molecular sciences · 2025Article
- 2dSpAn-Auto: an automated tool for analysis of two-dimensional dendritic spine images.BMC bioinformatics · 2025Article
- SpyDen: simplifying molecular and structural analysis across spines and dendrites.Bioinformatics (Oxford, England) · 2025Article
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- VSOT: volume-surface optimization for accurate ultrastructure analysis of dendritic spines.Bioinformatics (Oxford, England) · 2025Article
- Brief sleep disruption alters synaptic structures among hippocampal and neocortical somatostatin-expressing interneurons.bioRxiv : the preprint server for biology · 2025Article
- Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation.Frontiers in neuroinformatics · 2025Review
- Challenges and opportunities in engineering next-generation 3D microelectronic devices: improved performance and higher integration density.Nanoscale advances · 2024Review
- A FAIR, open-source virtual reality platform for dendritic spine analysis.Patterns (New York, N.Y.) · 2024Article
- Distinct forms of structural plasticity of adult-born interneuron spines in the mouse olfactory bulb induced by different odor learning paradigms.Communications biology · 2024Article
- Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders.Frontiers in neuroscience · 2024Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Dendritic spines form most excitatory synaptic inputs in neurons and these spines are altered in many neurodevelopmental and neurodegenerative disorders. Reliable methods to assess and quantify dendritic spines morphology are needed, but most existing methods are subjective and labor intensive. To solve this problem, we developed an open-source software that allows segmentation of dendritic spines from 3D images, extraction of their key morphological features, and their classification and clustering. Instead of commonly used spine descriptors based on numerical metrics we used chord length distribution histogram (CLDH) approach. CLDH method depends on distribution of lengths of chords randomly generated within dendritic spines volume. To achieve less biased analysis, we developed a classification procedure that uses machine-learning algorithm based on experts' consensus and machine-guided clustering tool. These approaches to unbiased and automated measurements, classification and clustering of synaptic spines that we developed should provide a useful resource for a variety of neuroscience and neurodegenerative research applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.