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Document type:
Journal Article 
Author(s):
Capobianco, Nicolò; Sibille, Ludovic; Chantadisai, Maythinee; Gafita, Andrei; Langbein, Thomas; Platsch, Guenther; Solari, Esteban Lucas; Shah, Vijay; Spottiswoode, Bruce; Eiber, Matthias; Weber, Wolfgang A; Navab, Nassir; Nekolla, Stephan G 
Title:
Whole-body uptake classification and prostate cancer staging in 68Ga-PSMA-11 PET/CT using dual-tracer learning. 
Abstract:
PURPOSE: In PSMA-ligand PET/CT imaging, standardized evaluation frameworks and image-derived parameters are increasingly used to support prostate cancer staging. Clinical applicability remains challenging wherever manual measurements of numerous suspected lesions are required. Deep learning methods are promising for automated image analysis, typically requiring extensive expert-annotated image datasets to reach sufficient accuracy. We developed a deep learning method to support image-based stagi...    »
 
Journal title abbreviation:
Eur J Nucl Med Mol Imaging 
Year:
2022 
Journal volume:
49 
Journal issue:
Pages contribution:
517-526 
Print-ISSN:
1619-7070 
TUM Institution:
Klinik und Poliklinik für Nuklearmedizin