Susceptibility to misdiagnosis of adversarial images by deep learning based retinal image analysis algorithms

Deep learning algorithms, typically implemented as Convolutional Neural Networks (CNNs), in recent years have gained traction in medical image analysis. The majority of CNNs employed in retinal image diagnosis applications are image-based; wherein input is the retinal image and output is the classification/diagnosis, resulting in a blackbox like algorithm. In contrast, hybrid lesion-based algorithms employ multiple CNN-based detectors to...