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

Research group

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

ISSN of the journal0363-9762

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Creation03/05/2021 10:29:00 AM

First validation03/05/2021 10:29:00 AM

Update time03/16/2023 12:38:06 AM

Status update03/16/2023 12:38:05 AM

Last indexation05/06/2024 7:37:14 AM

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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