QuPath

Import the whole slide image into QuPath.

Use annotation tools to define tumor regions.

Apply cell detection algorithms to identify lymphocytes.

Classify lymphocytes based on their proximity to tumor cells.

Export the quantification data for statistical analysis.

Import images of treated and control tissue samples.

Use cell detection and segmentation algorithms to identify cells.

Measure cell proliferation markers (e.g., Ki-67) using stain separation and quantification.

Compare the proliferation rates between treated and control samples.

Generate reports and visualizations to present the results.

Import the IHC-stained tissue image into QuPath.

Use stain separation algorithms to isolate the IHC stain signal.

Define regions of interest (ROIs) within the tissue.

Measure the intensity of the IHC stain within the ROIs.

Calculate and export the protein expression levels for each ROI.

Import the brain tissue image into QuPath.

Use cell detection algorithms optimized for neuronal cells.

Measure cell size, shape, and other morphological features.

Calculate neuronal cell density in different brain regions.

Compare the cell density and morphology between different experimental groups.