Deep-Fake medical image (X-ray) using GAN

Abstract

The paper “CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning” presented that the possibility of cyber attach on medicla records which leads to a serious damage on medical diagnosis process. This paper simulates the hypothetical attack by creating deep-fake X-ray images (Source: Chest X-ray Images). The ResNet-18 model, which achieved 0.98 accuracy on the origianl dataset (performance on teritary classification), performned much worse by 0.63, 0.57 and 0.55 (100, 200, and 500 iterations) on the fake images created by GAN (Generative adversarial networks). The result reiterate the danger of deep learning-based methods.

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