ArticleFrontiers in neuroanatomy2019
Optimization of Traced Neuron Skeleton Using Lasso-Based Model.
Article in Frontiers in neuroanatomy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- A robust approach to 3D neuron shape representation for quantification and classification.BMC bioinformatics · 2023Article
- 3D Neuron Morphology Analysis.Research square · 2023Article
- NRRS: a re-tracing strategy to refine neuron reconstruction.Bioinformatics advances · 2023Article
- Tracing weak neuron fibers.Bioinformatics (Oxford, England) · 2023Article
- NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images.IEEE transactions on visualization and computer graphics · 2022Article
- Super-resolution Segmentation Network for Reconstruction of Packed Neurites.Neuroinformatics · 2022Article
- GTree: an Open-source Tool for Dense Reconstruction of Brain-wide Neuronal Population.Neuroinformatics · 2021Article
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11 authors.
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Abstract
Reconstruction of neuronal morphology from images involves mainly the extraction of neuronal skeleton points. It is an indispensable step in the quantitative analysis of neurons. Due to the complex morphology of neurons, many widely used tracing methods have difficulties in accurately acquiring skeleton points near branch points or in structures with tortuosity. Here, we propose two models to solve these problems. One is based on an L1-norm minimization model, which can better identify tortuous structure, namely, a local structure with large curvature skeleton points; the other detects an optimized branch point by considering the combination patterns of all neurites that link to this point. We combined these two models to achieve optimized skeleton detection for a neuron. We validate our models in various datasets including MOST and BigNeuron. In addition, we demonstrate that our method can optimize the traced skeletons from large-scale images. These characteristics of our approach indicate that it can reduce manual editing of traced skeletons and help to accelerate the accurate reconstruction of neuronal morphology.
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