PanoBrain Home PanoBrain Glossary Marker-Positive Cell Classification
Classification

Marker-Positive Cell Classification

Determining which cells express the marker of interest

Definition
The assignment of each segmented nucleus as positive or negative for a fluorescent marker based on intensity thresholds or trained classifiers applied to the co-registered signal channel.
Per-Nucleus Decision
Each segmented cell gets a positive/negative label
Threshold vs. Classifier
Simple cases use thresholds; complex cases need ML

Classification Methods

After nuclear segmentation identifies all cells, classification determines which are marker-positive:

  • Intensity thresholding — measure mean signal in the marker channel within each nucleus; cells above threshold are positive
  • Adaptive thresholding — threshold varies by brain region to account for background differences
  • Machine learning classifiers — StrataQuest's classifier engine uses multiple features (intensity, texture, size, context) for more robust classification

The choice of method depends on signal quality and the degree of background variation across the section.

Share This Term
Term Connections