Validation of Deep learning-based patient re-identification and use of adversarial techniques

• Grant number: 24/01336-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2024
• End date: February 28, 2026
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: João Paulo Papa
• Grantee: Maurício José Grapéggia Zanella
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
• Associated research grant: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID

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 purposes.