Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation
Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation
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
Objectives
To develop and test a Retina U-Net algorithm for the detection of primary lung tumors and associated metastases of all stages on FDG-PET/CT.
Methods
A data set consisting of 364 FDG-PET/CTs of patients with histologically confirmed lung cancer was used for algorithm development and internal testing. The data set comprised tumors...
Alternative Titles
Full title
Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation
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Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2812877631
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2812877631
Other Identifiers
ISSN
1432-1084,0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-022-09332-y
