Abstract: Adversarial Examples as Benchmark for Medical Imaging Neural Networks
Deep learning has been widely adopted as the solution of choice for a plethora of medical imaging applications, due to its state-of-the-art performance and fast deployment. Traditionally, the performance of a deep learning model is evaluated on a test dataset, originating from the same distribution as the training set. This evaluation method provides insight regarding the generalization ability of a model.
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