Skull stripping with purely synthetic data
Fuente:
arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866918017589313536 |
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| author | Park, Jong Sung Ha, Juhyung Thakur, Siddhesh Badea, Alexandra Bakas, Spyridon Garyfallidis, Eleftherios |
| author_facet | Park, Jong Sung Ha, Juhyung Thakur, Siddhesh Badea, Alexandra Bakas, Spyridon Garyfallidis, Eleftherios |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_07159 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Skull stripping with purely synthetic data Park, Jong Sung Ha, Juhyung Thakur, Siddhesh Badea, Alexandra Bakas, Spyridon Garyfallidis, Eleftherios Image and Video Processing Computer Vision and Pattern Recognition 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. |
| title | Skull stripping with purely synthetic data |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2505.07159 |