Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

Mostafapour, Samaneh; Gholamiankhah, Faeze; Dadgar, Habibollah; Arabi, Hossein; Zaidi, Habib

doi:10.1097/RLU.0000000000003585

Scientific article

English

Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

ContributorsMostafapour, Samaneh; Gholamiankhah, Faeze; Dadgar, Habibollah; Arabi, Hossein; Zaidi, Habib

Published inClinical Nuclear Medicine

Publication date2021

Abstract

This study evaluates the feasibility of direct scatter and attenuation correction of whole-body 68Ga-PSMA PET images in the image domain using deep learning.

Keywords

68Ga-PSMA
Attenuation correction
Deep learning
PET/CT
Whole body

Affiliation entities

Research groups

Imagerie Médicale (TEP et TEMP) (542)

Funding

Swiss National Science Foundation - SNRF 320030_176052
Autre - Fondation privée des HUG RC-06-01.

Citation (ISO format)

MOSTAFAPOUR, Samaneh et al. Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain. In: Clinical Nuclear Medicine, 2021. doi: 10.1097/RLU.0000000000003585

Article (Published version)

Identifiers

PID : unige:151812
DOI : 10.1097/RLU.0000000000003585
PMID : 33661195

Journal ISSN0363-9762

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Creation05/03/2021 10:29:00

First validation05/03/2021 10:29:00

Update16/03/2023 00:38:06

Status update16/03/2023 00:38:05

Last indexation31/10/2024 22:08:50

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Feasibility of Deep Learning-Guided Attenuation and Scatter Correction of Whole-Body 68Ga-PSMA PET Studies in the Image Domain

This study evaluates the feasibility of direct scatter and attenuation correction of whole-body 68Ga-PSMA PET images in the image domain using deep learning.

Technical informations