Plaque Assay: fields, figures and reviewed conditions¶

Open Home → Assays → Toxoplasma → Plaque Assay. Choose Plaque for plaque fields or Figure for published figures containing wells, panels and surrounding text. These inputs do not require a preceding Measure run. See the module map, the Plaque Assay tutorial and spacr.submodules.analyze_plaques() for the surrounding workflow.

Preview a plaque field¶

Choose the source folder and select an image in the preview picker.
Select Plaque mode. In Settings… → Plaque detection, choose the plaque checkpoint, diameter, flow threshold and cell-probability threshold. Use Model zoo… to inspect available models or Browse… for a local checkpoint. A model key is different from a detector backend: both the checkpoint and a compatible runtime must be available.
Run the preview and inspect the labels against the image. Counts and mean areas describe the proposed segmentation, so check merged plaques, missed plaques and non-plaque regions before interpreting them.
Inspect the object, probability and flow views when the chosen segmenter supplies those outputs. Missing flow output is not a zero-valued result.
Choose Use these settings to copy the tuned values into the form that the analysis run reads. A preview alone does not run the folder analysis.

The preview resolves local checkpoints without downloading them implicitly. When a model is absent, the panel explains what is missing and offers the appropriate download. Keep the selected model and settings with the results; bundled names the historical packaged checkpoint, not an alias for the current Model Zoo model.

Read a published figure¶

Select Figure mode. Supply a folder of figures, or use From a paper… to retrieve figures and legends from a DOI, PMID, PMC identifier or PDF into a new folder.
If the figure reader is missing, use the panel’s Install action. It installs the YOLO/OCR reader in its own backend environment under ~/.spacr/backends. Inspect the installation result before previewing.
In Settings… → Figure, choose the well detector, inference sizes and confidence cutoff; the text-reading settings are on the Text detection tab. Run preview finds wells and reads the figure text; this first pass does not segment the plaques.
Click a well in the image or a table row. Plaque preview segments that well with the plaque settings. Find plaques in all wells processes the detected wells in sequence; Cancel stops after the current well.
Compare the proposed condition with the nearby label and the relevant legend passage. Correct the condition, mark reviewed entries OK, and save the annotations. With Confirm annotations enabled, the run measures only the saved approved entries.
Copy the tuned settings into the form before starting the analysis run. Retain the original figure, legend, annotation review and calibration information alongside the measurements.

The preview saves condition reviews in figure_annotations.csv and pasted legends in legends.csv in the source folder, preserving other figures’ entries. The batch figure workflow uses these files and writes its database under <src>/plaque_figures/plaque_figures.db by default. Reprocessing a figure replaces its previous rows; duplicate image content is recorded rather than counted as an independent image. See spacr.plaque_papers.measure_figure_folder() for the full file contract.

Areas in pixels and calibrated areas are different quantities. Verify the reported scale and its source before comparing physical areas between images. A detector box or an automatically read condition is a proposal to inspect, not evidence that the experimental identity or calibration is correct.

For a figure crop, its own labeled scale bar takes priority, followed by its own unlabeled bar whose length is stated in the legend. A crop without its own bar can share an agreeing calibration from similarly sized crops in the same grid. Conflicting peer bars leave that crop in pixels with a conflict note. Whole-well calibration is a later fallback when the plate format is known; stated magnification alone does not calibrate a rescaled figure.

Optional scale and time estimates¶

In Figure mode, enter any known Pixels per µm and formation time for each well first. Choose Estimate scale / time (experimental) to show suggestions in the Estimated pixels per µm, Estimated time (hours) and Estimate basis columns. Review the basis alongside each suggestion. The option is off by default and keeps suggestions separate from entered calibration and measured results.

The calculation uses the largest quarter of plaques and assumes linear diameter growth. Its default reference is an RH/HFF control diameter of about 894 µm at seven days. This reference does not establish a growth curve across times or conditions. When both scale and time are unknown, the reference duration is assumed; it is not a separately measured time. Conflicting known times prevent pooling wells into one page estimate.

Use Experimental Growth Estimates settings to choose a reference diameter and its corresponding duration for your experiment. Keep the reference and assumptions with exported suggestions. See spacr.plaque_growth.estimate_page() for the input and output fields.

Changing selections while a preview runs¶

Changing the source, selected image or mode abandons the previous preview. Its late result cannot replace the newly selected view. An empty source folder clears the prior mask, object views and figure tables. Start a new preview for the intended selection after it loads. Cancellation discards the old result; the current model call finishes before Run preview and the well controls become available again. Wait for those controls before rerunning with changed settings.

After choosing Save annotations, wait for the saved confirmation in the preview status before starting the batch analysis. Saving happens in the background so the image remains responsive; a queued save is not yet a completed write.

Python preview contracts¶

The same operations are available as worker-safe functions; they do not touch widgets. Their returned data is preview output, separate from the batch analysis database.

Function	Result and scope
`spacr.qt.widgets.plaque_preview.plaque_pass()`	Segment one plaque image and return labels, counts, areas and available flow outputs.
`spacr.qt.widgets.plaque_preview.detect_figure()`	Find figure regions and read text without segmenting plaques.
`spacr.qt.widgets.plaque_preview.prepare_figure_review()`	Read saved review information and propose ruler calibration for the detected figure while preserving supplied manual edits.
`spacr.qt.widgets.plaque_preview.segment_well()`	Segment a selected well crop with the plaque settings.
`spacr.qt.widgets.plaque_preview.figure_pass()`	Find, read and segment a figure in one function call. This differs from the GUI’s initial detection-only preview.

With the default segmenter, plaque_pass, segment_well and figure_pass use spacr.plaque.segment_plaque_image(), including the configured diameter, flow_threshold, CP_prob and channel-axis policy. A custom segment callback supplies its own segmentation behavior. Keep those settings explicit when comparing Python results with the GUI.

For GUI integrations, PlaquePreviewPanel.preview_running() remains true while a cancelled worker is finishing. set_preview_busy(False) therefore keeps rerun controls disabled until that worker exits. save_annotations() returns the queued destination; observe the preview status for completion or failure before consuming the file.