A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography

A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography

Three-dimensional transesophageal echocardiography (3DTEE) is the recommended imaging technique for the assessment of mitral valve (MV) morphology and lesions in case of mitral regurgitation (MR) requiring surgical or transcatheter repair. Such assessment is key to thorough intervention planning and...

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Bibliographic Details
Main Authors: Riccardo Munafo, Simone Saitta, Giacomo Ingallina, Paolo Denti, Francesco Maisano, Eustachio Agricola, Alberto Redaelli, Emiliano Votta
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
3D transesophageal echocardiography
mitral regurgitation
automatic segmentation
convolutional neural network
mitral valve anatomy quantification
mitral valve
Online Access:https://ieeexplore.ieee.org/document/10380557/

Internet

https://ieeexplore.ieee.org/document/10380557/

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