VolkCell Guide
A practical guide to VolkCell.
A practical field guide for running analyses, reviewing results, correcting masks, training custom models, managing experiments, and exporting data from VolkCell.
Fastest path
- 1. Open Analysis.
- 2. Upload representative microscopy images.
- 3. Pick the closest protocol/model settings.
- 4. Review counts, masks, CSVs, and overlays.
- 5. If needed, correct masks and train a custom model.
01 · Home
Use Home as your workspace overview
What it shows
- Your signed-in workspace and recent activity.
- Counts for active jobs, completed jobs, and available models.
- Quick-access experiment cards for the workflows enabled for your account.
What to click
- Run a quick analysis for a simple upload-and-count job.
- Quick access cards when you want protocol-specific experiment structure.
- Recent activity to reopen a prior job and download results.
02 · Analysis
Run a quick cell-count analysis
Choose the right images
Use representative brightfield or phase-contrast microscopy images. Keep acquisition settings consistent within a job where possible. Avoid mixing very different objectives, stains, or protocols unless you are intentionally stress-testing a model.
Select the closest workflow settings
Pick adherent/count-only settings for monolayer or plate-chamber style counting, suspension settings for floating cells, and live/dead or multiclass modes only when the images support those outputs.
Set calibration when scale matters
If you need density or area-normalized outputs, enter the calibration metadata or rely on extracted scale metadata when available. If you only need raw cell counts, calibration is optional.
Submit and wait for processing
Small jobs usually finish quickly. Larger image sets may sit in pending/processing while queue capacity, GPU startup, or file preparation completes. You can leave the page and reopen the job from recent activity.
03 · Results & corrections
Review outputs before trusting them
Counts
Start with totals and per-image counts. Look for obvious outliers before exporting or training from the run.
Masks & overlays
Use overlays to spot missed cells, merged clusters, debris, or scale-bar artifacts. The visual check is the quality gate.
Corrections
Edit masks when the model is wrong, save corrections, then use those corrected images as training signal.
- Correct enough diverse examples to cover normal images, crowded areas, faint cells, debris, and edge cases.
- Do not train from sloppy corrections: the model learns exactly what you save.
- Keep raw outputs and corrected outputs separate when reporting validation results.
04 · Training
Train a protocol-specific model when the default is not enough
Training adapts VolkCell to your cells, microscope, and segmentation preferences. It should follow inspection and correction, not replace it.
Recommended flow
- Run an analysis on representative images.
- Open the job and correct masks.
- Start a training session from the corrected job.
- Train, test on held-out images, inspect benchmark metrics.
- Save/promote the model only when validation is acceptable.
When not to train
- The default masks already match your counting rule.
- You only have one or two corrected images.
- Your corrections are inconsistent between reviewers.
- You need a validated model today but have no holdout images.
05 · Experiments
Use Experiments for structured scientific runs
Experiments group datasets, protocols, model runs, galleries, benchmark reports, and notes so analyses are traceable rather than one-off files.
Counting workflows
Best for routine adherent or suspension counts where consistent per-image totals matter.
Growth/timepoint workflows
Best for treatment studies, timepoints, and plate-level comparisons.
Morphology workflows
Best for protocol-specific morphology review, scoring, or model-development datasets.
Start with the workflow card that matches the biological question, then attach analyses and reports to that experiment.
06 · Models
Choose models conservatively
Built-in models are the safest starting point for exploratory analysis and first-pass counting.
Experimental custom models are useful for iteration, but treat them as unvalidated until they perform well on held-out images.
Validated custom models should be tied to a protocol, imaging setup, and benchmark report. Do not assume a model validated for one cell type or objective transfers to another.
07 · Exports
Export the right artifact for the job
CSV exports
Use CSVs for count tables, summaries, downstream statistics, and sharing compact results with collaborators.
Mask/overlay bundles
Use bundles when you need to audit segmentation quality, preserve visual evidence, or hand off correction tasks.
Experiment reports
Use reports for protocol-level summaries, benchmark interpretation, and customer-facing validation narratives.
Billing/internal exports
Internal accounts may see billing CSV access in the profile menu for usage review.
08 · Troubleshooting
Common problems and what to do
- Counts look too high.
- Check overlays for debris, split cells, or scale-bar/text artifacts being counted. Try a more appropriate analysis mode or correct masks before training.
- Counts look too low.
- Look for faint cells, low contrast, crowded clusters, or mismatched model/protocol settings. Add representative corrections and retrain if the pattern repeats.
- Job appears stuck.
- Large jobs and GPU-backed training can pause while files prepare or workers start. Refresh the job from recent activity. If it remains stalled, contact support with the job ID.
- Model is not in the picker.
- Confirm you are signed in with the same email used to train/save it, and that the model was promoted after validation.