Extended Data Fig. 3: Performance benchmarking of Cellpose2 and CellSighter for separate task.

Each method was evaluated for its originally intended task, namely Cellpose2 for segmentation and CellSighter for cell classification. Colorectal cancer CODEX dataset was used for benchmarking purpose. a) AP value of segmentation across a range of IoU thresholds. Each data point represents the average AP from a 10-fold cross-validation experiment. Band width around each line represents the standard deviation. Mean and standard deviation of average AP values across IoU thresholds are shown in the parenthesis. b) Heatmap showing the confusion matrix of CellSighter cell type classification results. Ground truth cell segmentation masks were used as input to CellSighter. Each grid in the heatmap includes an accuracy score and the count of cells. c) Barplot showing the precision for each class identified by the CellSighter model based on the ground truth cell segmentation mask, with an overall mean precision of 0.53.