MITS-GAN: Safeguarding medical imaging from tampering with generative adversarial networks

Giovanni Pasqualino, Luca Guarnera, Alessandro Ortis, Sebastiano Battiato

Abstract: Highlights•We tackle the critical issue of image manipulation in the field of medical imaging.•It protects images from tampering preserving their authenticity and reliability.•It emphasizes the need for measures to safeguard the integrity of medical scans.