Slice-selective learning for Alzheimer’s disease classification using a generative adversarial network: a feasibility study of external validation

Purpose The aim of this feasibility study was to use slice selective learning using a Generative Adversarial Network for external validation. We aimed to build a model less sensitive to PET imaging acquisition environment, since differences in environments negatively influence network performance. To investigate the slice performance, each slice evaluation was performed.