Fig. 1

Illustration of the methodology used to classify whole slide images into ODx risk categories. 1) Image patches are extracted at 40× from regions within whole slides identified by pathologists as containing invasive cancer. 2) Nuclei detection is performed on these image patches and 3) combined with a Deep Learning epithelial/stromal separation model. 4) Nuclear architecture and shape features are extracted from the detected epithelial and stromal nuclei separately. These features are combined with (5) a trained classification model in order predict the ODx risk category for each patch. Classification results from the image patches for each patient are (6) combined in a patch-based-voting method to (7) yield the final risk prediction on a patient level