Systems and methods facilitate privacy-preserving data curation in a federated learning system by transmitting a portion of a potential data sample to a remote location. The portion is inspected for quality to rule out data samples that do not satisfy data curation criteria. The remote examination focuses on checking the region of interest but maintains privacy as the examination is unable to parse any other identifiable subject information such as face, body shape etc. because pixels or voxels outside the portion are not included. The examination results are sent back to the collaborators so that inappropriate data samples can be excluded during federated learning rounds.