ArticleBioinformatics (Oxford, England)2021
Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling.Briefings in bioinformatics · 2024Article
- Machine learning approach for recognition and morphological analysis of isolated astrocytes in phase contrast microscopy.Scientific reports · 2024Article
- CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations.Neuroinformatics · 2023Article
- Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience.Briefings in bioinformatics · 2023Article
- Construction and imaging of a neurovascular unit model.Neural regeneration research · 2022Review
- Robust quasi-uniform surface meshing of neuronal morphology using line skeleton-based progressive convolution approximation.Frontiers in neuroinformatics · 2022Article
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Authors and funding
9 authors.
Funding
Abstract
motivationAstrocytes, the most abundant glial cells in the mammalian brain, have an instrumental role in developing neuronal circuits. They contribute to the physical structuring of the brain, modulating synaptic activity and maintaining the blood-brain barrier in addition to other significant aspects that impact brain function. Biophysically, detailed astrocytic models are key to unraveling their functional mechanisms via molecular simulations at microscopic scales. Detailed, and complete, biological reconstructions of astrocytic cells are sparse. Nonetheless, data-driven digital reconstruction of astroglial morphologies that are statistically identical to biological counterparts are becoming available. We use those synthetic morphologies to generate astrocytic meshes with realistic geometries, making it possible to perform these simulations.
resultsWe present an unconditionally robust method capable of reconstructing high fidelity polygonal meshes of astroglial cells from algorithmically-synthesized morphologies. Our method uses implicit surfaces, or metaballs, to skin the different structural components of astrocytes and then blend them in a seamless fashion. We also provide an end-to-end pipeline to produce optimized two- and three-dimensional meshes for visual analytics and simulations, respectively. The performance of our pipeline has been assessed with a group of 5000 astroglial morphologies and the geometric metrics of the resulting meshes are evaluated. The usability of the meshes is then demonstrated with different use cases. AVAILABILITY AND IMPLEMENTATION: Our metaball skinning algorithm is implemented in Blender 2.82 relying on its Python API (Application Programming Interface). To make it accessible to computational biologists and neuroscientists, the implementation has been integrated into NeuroMorphoVis, an open source and domain specific package that is primarily designed for neuronal morphology visualization and meshing. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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