Abstract
This proposal aims to validate and discuss data and personal security qualms about the spread of chest radiography datasets and anonymity breaching by patient re-identification and verification. This project will investigate techniques based on deep learning and adversarial learning to provide more secure images while not adding artifacts that may prevent them from being used for initial …