Tianyu Han

MoPaDi generates counterfactual explanations for histopathology images to reveal morphological features driving classifier predictions, improving interpretability in digital pathology.

This paper evaluates adversarial robustness of CNNs and ViTs in computational pathology, finding ViTs are more robust to attacks.

This paper introduces a method to generate high-resolution artificial radiographs using generative models to overcome data sharing barriers in medicine.