Progressive trajectory matching for medical dataset distillation

arXiv:2403.13469v1 Announce Type: new
Abstract: It is essential but challenging to share medical image datasets due to privacy issues, which prohibit building foundation models and knowledge transfer. In this paper, we propose a novel dataset distillation method to condense the original medical image datasets into a synthetic one that preserves useful information for building an analysis model without accessing the original datasets. Existing methods tackle only natural images by randomly matching parts of the training trajectories of the model parameters …

abstract arxiv building cs.cv dataset datasets distillation foundation image image datasets information knowledge medical novel paper privacy synthetic trajectory transfer type