Assessment of the Deep Learning-based Attenuation Correction in the Image Domain for 68Ga-PSMA PET Imaging using Artifact-free Dataset-Reference-Cited by-同舟云学术

Assessment of the Deep Learning-based Attenuation Correction in the Image Domain for 68Ga-PSMA PET Imaging using Artifact-free Dataset

Published:2022-11-05 Issue: Volume:28 Page:1-3
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Container-title:2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
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Author:

Giv Masoumeh Dorri¹,Kakhki Vahid Reza Dabbagh¹,Noroozbeigi Nasim²,Golestani Zahra Bakhshi²,Aghaee Atena¹,Dadgar Habibollah³,Mostafapour Samaneh⁴,Arabi Hossein⁵,Zaidi Habib⁵

Affiliation:

1. Mashhad University of Medical Sciences,Nuclear Medicine Research Center,Mashhad,Iran

2. Imam Reza International University,Razavi Cancer Research Center, Razavi Hospital,Iran

3. Imam Reza International University,Cancer Research Center, Razavi Hospital,Mashhad,Iran

4. University Medical Center Groningen,Department of Nuclear Medicine and Molecular Imaging,Groningen,Netherlands

5. Geneva University Hospital,Division of Nuclear Medicine & Molecular Imaging,Geneva,Switzerland,CH-1211

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10398888/10398889/10398951.pdf?arnumber=10398951

Reference18 articles.

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

2. Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET–MRI-guided radiotherapy treatment planning

3. Magnetic resonance imaging-guided attenuation correction in whole-body PET/MRI using a sorted atlas approach

4. One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI

5. Whole-body bone segmentation from MRI for PET/MRI attenuation correction using shape-based averaging