Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT
Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT
About this item
Full title
Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
Purpose
This study proposes an automated prostate cancer (PC) lesion characterization method based on the deep neural network to determine tumor burden on
68
Ga-PSMA-11 PET/CT to potentially facilitate the optimization of PSMA-directed radionuclide therapy.
Methods
We collected
68
Ga-PSMA-11 PET/CT images from 193 patients with...
Alternative Titles
Full title
Deep neural network for automatic characterization of lesions on 68Ga-PSMA-11 PET/CT
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2322805125
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2322805125
Other Identifiers
ISSN
1619-7070
E-ISSN
1619-7089
DOI
10.1007/s00259-019-04606-y
