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Vision-language foundation model for echocardiogram interpretation

Medicine and Health

Vision-language foundation model for echocardiogram interpretation

M. Christensen, M. Vukadinovic, et al.

Discover the groundbreaking research by Matthew Christensen, Milos Vukadinovic, Neal Yuan, and David Ouyang on EchoCLIP, a cutting-edge model for echocardiography that elevates cardiac imaging interpretation. With its remarkable ability to assess cardiac function and identify devices, this model is set to transform how clinicians work with echocardiograms.

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Playback language: English
Abstract
This paper introduces EchoCLIP, a vision-language foundation model for echocardiography, trained on a large dataset of cardiac ultrasound videos and corresponding expert interpretations. EchoCLIP demonstrates strong performance on various benchmarks for cardiac image interpretation, including assessing cardiac function, identifying implanted devices, and identifying unique patients across multiple videos. A long-context variant, EchoCLIP-R, further enhances these capabilities, enabling accurate clinical transition identification and robust image-to-text search. This research represents a significant advancement in applying foundation models to cardiovascular imaging for preliminary echocardiographic interpretation.
Publisher
Nature Medicine
Published On
May 01, 2024
Authors
Matthew Christensen, Milos Vukadinovic, Neal Yuan, David Ouyang
Tags
EchoCLIP
echocardiography
cardiac imaging
foundation model
cardiac ultrasound
image interpretation
clinical application
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