Specific improvements or additions in the new release include:

Cell image synthesis
  • Improved vesicular organelles model
    • Eliminate object/object and object/boundary overlap during generation
  • Ability to combine models learned from images of different resolution, and synthesize images at desired resolution
  • Ability to synthesis random walks in shape space from diffeomorphic models of cell and nuclear shape
    • Including directed random walks using Willmore energy and shape space density
Model training
  • New capabilities for cell and nuclear shape model learning
    • Build nuclear models from images without nuclear marker
    • Build joint diffeomorphic models of cell and nuclear shape
  • Per-cell representations for easy model building and comparison
  • Export to SBML-spatial and mesh formats for interfacing with tools such as CellBlender and VCell
  • Parallelization of model learning pipeline
  • Reporter tools
    • Assess learned models
    • Compare models
    • Compare per cell parameters within or across models





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