URFM: a general Ultrasound Representation Foundation Model for advancing ultrasound image diagnosis

Abstract excerpt

<title>Abstract</title> <p>Ultrasound imaging is pivotal in clinical diagnostics, providing critical insights into a wide range of diseases and organs. However, advancing artificial intelligence (AI) in this field is hindered by challenges such as the reliance on large labeled datasets and the limited generalizability of task-specific models, largely due to ultrasound’s low signal-to-noise ratio (SNR). To address...

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Identifiers and source

Literature Corpus work

f62319e9-0ea2-513e-889d-654a45a68207

DOI

10.21203/rs.3.rs-5662163/v1