Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neura...
Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks
About this item
Full title
Author / Creator
Erdil, Ertunc , Becker, Anton S. , Schwyzer, Moritz , Martinez-Tellez, Borja , Ruiz, Jonatan R. , Sartoretti, Thomas , Vargas, H. Alberto , Burger, A. Irene , Chirindel, Alin , Wild, Damian , Zamboni, Nicola , Deplancke, Bart , Gardeux, Vincent , Maushart, Claudia Irene , Betz, Matthias Johannes , Wolfrum, Christian and Konukoglu, Ender
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
The standard method for identifying active Brown Adipose Tissue (BAT) is [
18
F]-Fluorodeoxyglucose ([
18
F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed with computational methods that predict [
18
F]-FDG uptake by BAT from CT;...
Alternative Titles
Full title
Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks
Authors, Artists and Contributors
Author / Creator
Becker, Anton S.
Schwyzer, Moritz
Martinez-Tellez, Borja
Ruiz, Jonatan R.
Sartoretti, Thomas
Vargas, H. Alberto
Burger, A. Irene
Chirindel, Alin
Wild, Damian
Zamboni, Nicola
Deplancke, Bart
Gardeux, Vincent
Maushart, Claudia Irene
Betz, Matthias Johannes
Wolfrum, Christian
Konukoglu, Ender
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_c805cb8195b94f0d8b4205323cae48a9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c805cb8195b94f0d8b4205323cae48a9
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-024-52622-w
