Adversary-Robust Graph-Based Learning of WSIs

Summary

The authors propose a graph-based defense model for whole slide images (WSIs) used in cancer diagnosis. It combines a graph neural network, a denoising module based on untrained neural network prior and graph signal processing, and a vision transformer for prostate cancer Gleason grading. Tested against various adversarial attacks, the model showed a significant improvement in diagnosis accuracy.

Topics

• Adversarial machine learning

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