Goals and scope for CellCanvas

I am creating this issue to discuss our goals and scope for CellCanvas.

From my perspective, CellCanvas is a software library for building geometric models of intracellular architecture. These models can be used for quantifying and comparing morphology as well as for input into simulations.

The core library contains:
- geometric models for all key intracellular components. This includes meshes (e.g., for membranes), networks of splines (e.g., for filaments), and particles (both position and orientation).
- data models for defining collections of the geometric models
- algorithms for extracting the models from imaging data (e.g., segmentation, pixel embeddings)
- a graphical user interface for extracting and building the models from images

Non-goals:
- provide state-of-the-art performance for all computer vision tasks. I think we should provide solid implementations of some core tasks, but also make it easy for users to import results from other algorithms
- perform simulations. I think we should be able to export the geometries to simulation software easily, but I don't think we need to have any sort of simulation engine in the core.

No files, tests, or entry points are named. Start by reading the issue discussion and repository overview to understand the proposed library boundaries; the issue does not define a concrete change or a verifiable done condition.

Written by the indexing model from the issue text.