An automated pipeline segments the MitraClip in 3D transesophageal echocardiography, classifies its opening angle into ten configurations, and refines the result with CAD template registration, achieving 0.75 mm average surface distance and 0.74 weighted F1 on a simulator test set.
A deep learning-based fully automated pipeline for regurgitant mitral valve anatomy analysis from 3d echocar- diography,
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MitraClip Device Automated Localization in 3D Transesophageal Echocardiography via Deep Learning
An automated pipeline segments the MitraClip in 3D transesophageal echocardiography, classifies its opening angle into ten configurations, and refines the result with CAD template registration, achieving 0.75 mm average surface distance and 0.74 weighted F1 on a simulator test set.