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Skull stripping with purely synthetic data

2025-05-12Code Available0· sign in to hype

Jong Sung Park, Juhyung Ha, Siddhesh Thakur, Alexandra Badea, Spyridon Bakas, Eleftherios Garyfallidis

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Abstract

While many skull stripping algorithms have been developed for multi-modal and multi-species cases, there is still a lack of a fundamentally generalizable approach. We present PUMBA(PUrely synthetic Multimodal/species invariant Brain extrAction), a strategy to train a model for brain extraction with no real brain images or labels. Our results show that even without any real images or anatomical priors, the model achieves comparable accuracy in multi-modal, multi-species and pathological cases. This work presents a new direction of research for any generalizable medical image segmentation task.

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