Ultraliser

Ultraliser generates high-fidelity, biologically realistic multiscale 3D models of neuroscientific structures, from mitochondria and endoplasmic reticula to neurons, glia, cerebral vasculature, and minicolumns, for quantitative and simulation-based studies.

Key Features:

• Multiscale modeling: Produces models across scales from intracellular components (mitochondria, endoplasmic reticula) through cellular elements (neurons, glia) to multicellular assemblies (cerebral vasculature, minicolumns).
• Output formats: Exports triangulated surface meshes and annotated volumes suitable for in silico neuroscience.
• Voxelization engine: Uses an advanced voxelization engine to ensure high performance and robustness when processing inputs.
• Input processing: Processes arbitrary non-watertight triangular soups, digitized morphological skeletons, and binary volumetric masks as inputs.
• Watertight mesh generation: Produces optimized watertight surface meshes and annotated voxel grids from diverse input types.
• Quantitative geometry: Generates geometrically precise and biologically plausible models enabling precise quantification of surface areas and volumes.
• Scalability: Supports scalable supercomputer simulations by producing optimized meshes and annotated voxel grids suitable for large-scale studies.
• Subcellular simulation readiness: Produces detailed models required for subcellular simulations and analyses of structure–function relationships.

Scientific Applications:

• Multiscale structural modeling: Enables reconstruction and analysis of structures from organelles to multicellular assemblies for mechanistic studies.
• Subcellular simulations: Supports simulations at subcellular scales, including investigations relevant to cell signaling mechanisms.
• Quantitative parameter estimation: Provides precise measurements of surface areas and volumes for cellular and system-level simulation parameters.
• Large-scale simulation studies: Facilitates generation of hundreds of models for diverse simulation applications and scalable supercomputer experiments.

Methodology:

Advanced voxelization engine converts arbitrary non-watertight triangular soups, digitized morphological skeletons, and binary volumetric masks into optimized watertight triangulated surface meshes and annotated voxel grids/volumes.