Abdellah, MarwanGuerrero, Nadir RomanLapere, SamuelCoggan, Jay S.Keller, DanielCoste, BenoitDagar, SnigdhaCourcol, Jean-DenisMarkram, HenrySchurmann, Felix2021-06-192021-06-192021-06-192020-07-0110.1093/bioinformatics/btaa461https://infoscience.epfl.ch/handle/20.500.14299/178946WOS:000579894600063Motivation: Accurate 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.Results: We 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.Biochemical Research MethodsBiotechnology & Applied MicrobiologyComputer Science, Interdisciplinary ApplicationsMathematical & Computational BiologyStatistics & ProbabilityBiochemistry & Molecular BiologyComputer ScienceMathematics3d visualizationreconstructionsegmentationtext::journal::journal article::research article