A convolutional neural network for total tumor segmentation in [64Cu]Cu-DOTATATE PET/CT of patients with neuroendocrine neoplasms

Abstract Background Segmentation of neuroendocrine neoplasms (NENs) in [64Cu]Cu-DOTATATE positron emission tomography makes it possible to extract quantitative measures useable for prognostication of patients. However, manual tumor segmentation is cumbersome and time-consuming. Therefore, we aimed t...

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Autori principali:	Esben Andreas Carlsen, Kristian Lindholm, Amalie Hindsholm, Mathias Gæde, Claes Nøhr Ladefoged, Mathias Loft, Camilla Bardram Johnbeck, Seppo Wang Langer, Peter Oturai, Ulrich Knigge, Andreas Kjaer, Flemming Littrup Andersen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	SpringerOpen 2022-05-01
Serie:	EJNMMI Research
Soggetti:	Tumor segmentation Artificial intelligence Neuroendocrine neoplasms [64Cu]Cu-DOTATATE PET Prognostication
Accesso online:	https://doi.org/10.1186/s13550-022-00901-2
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