Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET.
AI
FET PET
artificial intelligence
machine learning
neurooncology
volumetry
Journal
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
ISSN: 1535-5667
Titre abrégé: J Nucl Med
Pays: United States
ID NLM: 0217410
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
14
03
2023
revised:
31
05
2023
medline:
5
10
2023
pubmed:
11
8
2023
entrez:
10
8
2023
Statut:
ppublish
Résumé
Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas.
Identifiants
pubmed: 37562802
pii: jnumed.123.265725
doi: 10.2967/jnumed.123.265725
doi:
Substances chimiques
Amino Acids
0
Radiopharmaceuticals
0
Tyrosine
42HK56048U
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1594-1602Informations de copyright
© 2023 by the Society of Nuclear Medicine and Molecular Imaging.