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

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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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: SpringerOpen 2022-05-01
Series:EJNMMI Research
Subjects:
Tumor segmentation
Artificial intelligence
Neuroendocrine neoplasms
[64Cu]Cu-DOTATATE PET
Prognostication
Online Access:https://doi.org/10.1186/s13550-022-00901-2

Internet

https://doi.org/10.1186/s13550-022-00901-2

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