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Title

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

Authors
Hatt, Mathieu
Lee, John A
Schmidtlein, Charles R
Naqa, Issam El
Caldwell, Curtis
De Bernardi, Elisabetta
Lu, Wei
Das, Shiva
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Published in Medical Physics. 2017, vol. 44, no. 6, p. e1-e42
Abstract The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.
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PMID: 28120467
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Article (Published version) (723 Kb) - document accessible for UNIGE members only Limited access to UNIGE
Structures
Research group Imagerie Médicale (TEP et TEMP) (542)
Projects FNS: SNF 31003A-149957
Swiss Cancer Research Foundation under Grant KFS-3855-02-2016
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(ISO format)
HATT, Mathieu et al. Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211. In: Medical Physics, 2017, vol. 44, n° 6, p. e1-e42. https://archive-ouverte.unige.ch/unige:99856

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Deposited on : 2017-11-30

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