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Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings
Not provided in the abstract
segmentationmachine learningultrasoundclinical applications
2609.19230
Builder Relevance
2h ago80%
Abstract
SonoCorpus and SonoBase provide a unified resource and model for robust ultrasound segmentation across diverse clinical settings.
Reality Card
Core Claim
SonoBase outperforms existing models in segmentation accuracy across various datasets and settings, including those with minimal training.
Method / Result
SonoBase achieves a 6.63% error in ejection fraction, within inter-observer variability.
Limitations
The paper does not specify potential limitations in reproducibility beyond the need for ultrasound-specific pretraining.
Paper to code
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