Figure 4.

(a) Example segmentation results from each model on the GlaS dataset. The first column displays the input image, and the ground truth label for the input image is shown in the second column. The remaining columns display the output from each model in comparison to the ground truth. Blue pixels correspond to the ground truth, and red pixels correspond to the predicted output. Light green pixels indicate that both the ground truth and predicted output agree. As shown here, all models perform comparatively well for this dataset. In some instances, the models with the histogram layers (i.e., JOSHUA and JOSHUA+) reduce the false positives identified by the other models. (b) Dice coefficient, IOU, cancerous glands tissue IOU, precision, recall, and specificity metrics for each model for GlaS dataset. Metrics are shown as $\text{mean}\pm \text{SD}$. A one-way analysis of variance followed by Dunnett’s multiple comparison test was computed. The asterisks ($\ast$) indicate significant differences as compared to UNET ($p<0.05$).