Why the study?
Does a deep learning pipeline automatically calculate pericardial effusion width from raw echocardiography clips?
Does a deep learning pipeline automatically calculate pericardial effusion width from raw echocardiography clips?
A novel deep learning pipeline can automatically calculate pericardial effusion width from echocardiography clips, potentially providing a standardized approach and reducing operator dependency.
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May standardize effusion measurement and reduce variability; leaves open prospective validation before clinical adoption.
The machine-learning pipeline developed in this study can automatically calculate the width of PE from raw ultrasound clips. The novel concepts of moving window view selection for image quality control and computer vision techniques for maximal PE width calculation seem useful in the field of ultrasound. This pipeline could potentially provide a standardized and objective approach to the measurement of PE, reducing operator-dependency and improving accuracy.
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Cheng et al. (2023) studied this question.
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