Oct. 3, 2022, 1:20 a.m. | Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama

cs.CR updates on arXiv.org arxiv.org

Sharing medical datasets between hospitals is challenging because of the
privacy-protection problem and the massive cost of transmitting and storing
many high-resolution medical images. However, dataset distillation can
synthesize a small dataset such that models trained on it achieve comparable
performance with the original large dataset, which shows potential for solving
the existing medical sharing problems. Hence, this paper proposes a novel
dataset distillation-based method for medical dataset sharing. Experimental
results on a COVID-19 chest X-ray image dataset show that …

medical sharing

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