Figure 1.

Processing pipeline of the proposed risk-aware Bayesian model. The Bayesian model outputs one predictive distribution per class (instead of the scalar outputs of the standard networks) whose mean and dispersion represents the network prediction and uncertainty, respectively. In the far right panel, the green (red) borders of the images illustrate the correct (incorrect) predictions of the automated model which is not always available as it requires manual annotation of samples by medical experts. The green (red) shaded areas, in contrast, depicts the regions where the model is certain (uncertain) about its prediction. Uncertainty is the natural output of the Bayesian model which serves as complementary information to refer the uncertain samples to experts and improve the overall prediction performance of the automated system.