Question on suitability of Morpheus for synthetic 3D cell ground-truth generation

[Caspar Amery]

Dear,

I hope you are doing well, and I wish you a happy holiday season and a great start to the new year.

I am a master’s student in Computer Science (AI specialization). I am currently working on my master’s thesis, which focuses on generating realistic synthetic microscopy data to train AI models for cell segmentation.

I am reaching out because I am exploring whether Morpheus would be a good fit for one specific part of my pipeline, and I would greatly value your expert opinion.

Thesis goal (high-level)

My goal is not to study a specific biological process, but to generate realistic 3D ground truth of multiple interacting cells, which I then pass to a separate optics simulator to produce realistic 2D microscopy images. These images are used to train and evaluate AI segmentation models.

What I need from a 3D cell simulator

Concretely, I am looking for a simulator that can:

• Export a clean voxelized 3D grid
• Shape: (Z, Y, X) or (T, Z, Y, X)
• Values as either:
• instance labels (0 = background, 1..N = cell ID), or
• per-voxel density/intensity (fluorophore density), optionally with a parallel instance-ID volume
• Provide voxel size (dz, dy, dx) in µm (or enough metadata to derive it)
• Ideally export to NetCDF / OME-Zarr (xarray-friendly), but NumPy + sidecar metadata is also acceptable

Biological realism needed (focused & minimal)

• Realistic cell clustering and adhesion (this is the most important biological aspect for my use case)
• High diversity of cell morphologies (irregular, elongated, possibly branched shapes, ..; the more diverse the better)
• Temporal sequences with diverse deformations over time, to get diverse training data for models
  (cell division is note necessarily required)

Practical constraints

• ~50–150 cells 
• Typical volume size: 128 × 128 × 128 voxels
• Should run on a good desktop CPU/GPU
• Must be usable in headless / scripted batch mode for dataset generation

Optional but nice-to-have

• Multi-channel structure (e.g. whole cell + nucleus)

My question

Given this very specific goal (synthetic data generation for AI, not hypothesis-driven biology):

1. Would you consider Morpheus a good fit for this use case?
2. Can it naturally produce the kind of voxelized outputs described above, or would this require significant custom development?
3. If not ideal, would you recommend a different (possibly simpler) tool or workflow better suited for this purpose?
4. If it is a good fit: do you have recommendations on how to best get started for this specific use case (e.g. example models, settings, tutorials, or minimal workflows you would suggest focusing on)?

I fully understand if this use case falls somewhat outside the original scope of the tool, and I would greatly appreciate any honest guidance or redirection.

Thank you very much for your time, and again, warm wishes for the holidays and the upcoming new year.

[Lutz Brusch]

Happy New Year to all Morpheus Users and Welcome Caspar!

Your cell segmentation project is very relevant for multicellular biology research and yes, Morpheus simulations can provide realistic ground truth data for it. Moreover, Morpheus simulations also provide the true cell trajectories and genealogies of growing cell populations (as related topics for video microscopy data analysis). 

Regarding realistic cell shapes, please see previous models in the repository of published studies that relate to specific cell types and tissues: https://morpheus.gitlab.io/model/published-models/

You can further fine-tune the cell shapes and dynamics through a number of parameters, as explained in this model collection: https://morpheus.gitlab.io/category/l.-edelstein-keshet-mathematical-models-in-cell-biology/ 

We can also help if you need models for specific cell behaviours or shapes.

The simulated 3D cell shapes can be exported as 3D voxel lattice via 
1. Analysis/TiffPlotter with OME header as discussed in https://morpheus.gitlab.io/faq/analysis/3d-visualization/

or

2. Analysis/VtkPlotter as  discussed in https://morpheus.gitlab.io/courses/from-pde-to-tissue/convert-to-3d/

and in each case the channel attribute can be set to cell.id for unique cell shape identification.

A minimal model file with all 3D export options is attached here (and was derived from https://identifiers.org/morpheus/M0024, it starts from 4 cells and lets them divide to grow a cluster of ~150 cells, the lattice has your preferred size of 128^3). Please open the attached model file in a Morpheus GUI and click on Analysis (top left model tree) and then the respective Plotter (middle panel) to read the detailed documentation (displayed inside the Morpheus GUI in a panel on the right) for all the export options, formats and attributes. The 3D cubic lattice has integer coordinates and you can/have to assign any spatial unit post-hoc (e.g. using a script in Analysis/External). Trajectories of the centers of mass of all cells can be exported using Analysis/CellTracker. Also, please see the courses and videos for working with Morpheus: https://morpheus.gitlab.io/courses/

Many models in the repo (https://morpheus.gitlab.io/model/) use some intracellular model to dynamically change a CellProperty which can be exported as (another) channel and represent a (homogeneous cytosolic) fluorescence marker. So multi-channel data is possible.

To run simulations in batch mode, please see the command line --help for details. This for instance supports re-setting parameter values (like RandomSeed) and handling of the results files. 

All the best!

Lutz

for Morpheus.lab