Deep Convolutional Backbone Comparison for Automated PET Image Quality Assessment.
Convolutional neural networks
Deep learning
Image quality
Image reconstruction
Transfer learning
Journal
IEEE transactions on radiation and plasma medical sciences
ISSN: 2469-7311
Titre abrégé: IEEE Trans Radiat Plasma Med Sci
Pays: United States
ID NLM: 101705223
Informations de publication
Date de publication:
01 Aug 2024
01 Aug 2024
Historique:
medline:
15
10
2024
pubmed:
15
10
2024
entrez:
15
10
2024
Statut:
aheadofprint
Résumé
Pretraining deep convolutional network mappings using natural images helps with medical imaging analysis tasks; this is important given the limited number of clinically-annotated medical images. Many two-dimensional pretrained backbone networks, however, are currently available. This work compared 18 different backbones from 5 architecture groups (pretrained on ImageNet) for the task of assessing [
Identifiants
pubmed: 39404656
doi: 10.1109/TRPMS.2024.3436697
pmc: PMC7616552
doi:
Types de publication
Journal Article
Langues
eng