ArticleBioinformatics (Oxford, England)2020
Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- A Deep Learning Approach for Improving Two-Photon Vascular Imaging Speeds.Bioengineering (Basel, Switzerland) · 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
- High-resolution three-dimensional blood flow tomography in the subdiffuse regime using laser speckle contrast imaging.Journal of biomedical optics · 2022Article
- Evaluation of resonant scanning as a high-speed imaging technique for two-photon imaging of cortical vasculature.Biomedical optics express · 2022Article
- Robust quasi-uniform surface meshing of neuronal morphology using line skeleton-based progressive convolution approximation.Frontiers in neuroinformatics · 2022Article
- Digital Reconstruction of the Neuro-Glia-Vascular Architecture.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations.Bioinformatics (Oxford, England) · 2021Article
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10 authors.
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Abstract
motivationAccurate morphological models of brain vasculature are key to modeling and simulating cerebral blood flow in realistic vascular networks. This in silico approach is fundamental to revealing the principles of neurovascular coupling. Validating those vascular morphologies entails performing certain visual analysis tasks that cannot be accomplished with generic visualization frameworks. This limitation has a substantial impact on the accuracy of the vascular models employed in the simulation.
resultsWe present VessMorphoVis, an integrated suite of toolboxes for interactive visualization and analysis of vast brain vascular networks represented by morphological graphs segmented originally from imaging or microscopy stacks. Our workflow leverages the outstanding potentials of Blender, aiming to establish an integrated, extensible and domain-specific framework capable of interactive visualization, analysis, repair, high-fidelity meshing and high-quality rendering of vascular morphologies. Based on the initial feedback of the users, we anticipate that our framework will be an essential component in vascular modeling and simulation in the future, filling a gap that is at present largely unfulfilled. AVAILABILITY AND IMPLEMENTATION: VessMorphoVis is freely available under the GNU public license on Github at https://github.com/BlueBrain/VessMorphoVis. The morphology analysis, visualization, meshing and rendering modules are implemented as an add-on for Blender 2.8 based on its Python API (application programming interface). The add-on functionality is made available to users through an intuitive graphical user interface, as well as through exhaustive configuration files calling the API via a feature-rich command line interface running Blender in background mode. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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