Non-DAPI Independent Detection

Non-DAPI independent detection is for projects where marker-positive cells are detected directly from marker stainings such as cFos or TRAP.

Use it when there is no shared DAPI or nuclei-source population that should define the denominator.

Project setup

During project creation, choose the non-DAPI independent detection workflow.

Assign at least one staining as an Independent detection marker.

If the same staining should also provide anatomy for registration, assign it as the Anatomical reference too.

Upload one image per independent marker for each slice at the project detail magnification.

For high-res whole-slice projects, no 4x image is required.

For 4x reference + detail projects, upload the anatomical reference image plus marker detail images.

Training uses positive and negative examples, but the meaning is different from DAPI-based marker classification.

A positive example is an accepted marker-positive cell.
A negative example is a rejected detection candidate, false positive, or background.

A negative example is not a marker-negative biological population.

Results and Statistics count accepted marker-positive cells.

Use marker-positive cells and marker-positive cells/mm2 as the main metrics.

Do not interpret marker-positive proportions, negative cells, or all-cell density for independent-detection projects.

Review the raw detection behavior and classifier output visually.

A useful model should keep true marker-positive cells and reject obvious false positives or background candidates.