RT Journal Article
T1 Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants
A1 Gontard, Lionel C.
A1 Pizarro, Joaquín
A1 Sanz-Peña, Borja
A1 Lubián López, Simón P.
A1 Benavente-Fernández, Isabel
K1 Deep learning
K1 Birth weight
K1 Gestational age
K1 Premature infants
K1 Convolutional neural networks
K1 Ultrasonography
K1 Stroke Volume
K1 Aprendizaje profundo
K1 Peso al nacer
K1 Edad gestacional
K1 Recien nacido prematuro
K1 Red nerviosa
K1 Ultrasonografía
K1 Volumen sistólico
AB 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 automatic segmentation ventricular volume from 3D US of preterm infants with PHVD. The method was validated with the Dice similarity coefficient (DSC) and the intra-class coefficient (ICC) compared to manual segmentation. The mean birth weight of the included patients was 1233.1 g (SD 309.4) and mean gestational age was 28.1 weeks (SD 1.6). A total of 152 serial 3D US from 10 preterm infants with PHVD were analysed. 230 ventricles were manually segmented. Of these, 108 were used for training a 2D CNN and 122 for validating the methodology for automatic segmentation. The global agreement for manual versus automated measures in the validation data (n = 122) was excellent with an ICC of 0.944 (0.874-0.971). The Dice similarity coefficient was 0.8 (± 0.01). 3D US based ventricular volume estimation through an automatic segmentation software developed through deep learning improves the accuracy and reduces the processing time needed for manual segmentation using VOCAL. 3D US should be considered a promising tool to help deepen our current understanding of the complex evolution of PHVD.
PB Springer Nature
YR 2021
FD 2021-01-12
LK http://hdl.handle.net/10668/4363
UL http://hdl.handle.net/10668/4363
LA en
NO Gontard LC, Pizarro J, Sanz-Peña B, Lubián López SP, Benavente-Fernández I. Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants. Sci Rep. 2021 Jan 12;11(1):567
DS RISalud
RD Mar 14, 2025