U-Net-based image segmentation of the whole heart and four chambers on pediatric X-ray computed tomography.
Cardiac computed tomography
Deep learning
Heart
Pediatric
Segmentation
Journal
Radiological physics and technology
ISSN: 1865-0341
Titre abrégé: Radiol Phys Technol
Pays: Japan
ID NLM: 101467995
Informations de publication
Date de publication:
Jun 2022
Jun 2022
Historique:
received:
11
02
2022
accepted:
18
04
2022
revised:
17
04
2022
pubmed:
8
5
2022
medline:
14
6
2022
entrez:
7
5
2022
Statut:
ppublish
Résumé
This study aimed to determine whether a U-Net-based segmentation method could be used to automatically extract regions of the whole heart and atrioventricular regions from pediatric cardiac computed tomography images with high accuracy. Pediatric cardiac contrast computed tomography images with no abnormalities (n = 20; patient age, 0-13 years; mean 5 years) were used for segmentation of the whole heart and each atrioventricular region using U-Net. Segmentation accuracy was evaluated using the Dice similarity coefficient. The mean Dice similarity coefficient for the whole-heart segmentation was high at 0.95. There were no significant differences between age categories. The median Dice similarity coefficients for segmentation of the atria and ventricles were good (> 0.86). There were significant differences between age categories at some sites. Differences in the Dice similarity coefficient may have occurred because the target diseases and examination procedures differed according to subject age. There was no clear tendency for similar values between subjects of school age, close to adulthood, and newborns; good agreement was obtained in all age categories. These results suggest that U-Net-based segmentation may be useful for automatic extraction of the whole heart and atrioventricular regions from pediatric computed tomography images.
Identifiants
pubmed: 35524912
doi: 10.1007/s12194-022-00657-3
pii: 10.1007/s12194-022-00657-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
156-169Informations de copyright
© 2022. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.
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