Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants

To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We trained a 2D convolutional neural network (CNN) for a...

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Detalles Bibliográficos
Autores principales: Gontard, Lionel C., Pizarro, Joaquín, Sanz-Peña, Borja, Lubián López, Simón P., Benavente-Fernández, Isabel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803781/
https://www.ncbi.nlm.nih.gov/pubmed/33436974
http://dx.doi.org/10.1038/s41598-020-80783-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803781/
https://www.ncbi.nlm.nih.gov/pubmed/33436974
http://dx.doi.org/10.1038/s41598-020-80783-3

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