Cargando…

Post-reconstruction enhancement of [(18)F]FDG PET images with a convolutional neural network

BACKGROUND: The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images. METHODS: A convolutional neural network (CNN) was trained by using pairs of excellent (acquisitio...

Descripción completa

Detalles Bibliográficos
Autores principales:	Ly, John, Minarik, David, Jögi, Jonas, Wollmer, Per, Trägårdh, Elin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2021
Materias:	Original Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113431/ https://www.ncbi.nlm.nih.gov/pubmed/33974171 http://dx.doi.org/10.1186/s13550-021-00788-5

Ejemplares similares

The use of a proposed updated EARL harmonization of (18)F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations
por: Ly, John, et al.
Publicado: (2019)

Dose-reduced [(18)F]PSMA-1007 PET is feasible for functional imaging of the renal cortex
por: Valind, Kristian, et al.
Publicado: (2021)

[(18)F]PSMA-1007 PET is comparable to [(99m)Tc]Tc-DMSA SPECT for renal cortical imaging
por: Valind, Kristian, et al.
Publicado: (2023)

[(18)F]PSMA‐1007 renal uptake parameters: Reproducibility and relationship to estimated glomerular filtration rate
por: Valind, Kristian, et al.
Publicado: (2022)

Optimization of [(18)F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer
por: Trägårdh, Elin, et al.
Publicado: (2020)

Image reconstruction methods affect software-aided assessment of pathologies of [(18)F]flutemetamol and [(18)F]FDG brain-PET examinations in patients with neurodegenerative diseases
por: Lindström, Elin, et al.
Publicado: (2020)

Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for (18)F-FDG
por: Trägårdh, Elin, et al.
Publicado: (2019)

AI-based detection of lung lesions in [(18)F]FDG PET-CT from lung cancer patients
por: Borrelli, Pablo, et al.
Publicado: (2021)

Comparison of conventional and Si-photomultiplier-based PET systems for image quality and diagnostic performance
por: Oddstig, Jenny, et al.
Publicado: (2019)

Impact of penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm for (18)F-fluorocholine PET-CT regarding image quality and interpretation
por: Bjöersdorff, Mimmi, et al.
Publicado: (2019)

Detection of lymph node metastases in patients with prostate cancer: Comparing conventional and digital [(18)F]‐fluorocholine PET‐CT using histopathology as a reference
por: Bjöersdorff, Mimmi, et al.
Publicado: (2022)

PET/CT imaging 2 h after injection of [(18)F]PSMA-1007 can lead to higher staging of prostate cancer than imaging after 1 h
por: Hvittfeldt, Erland, et al.
Publicado: (2023)

Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth
por: Sartor, Hanna, et al.
Publicado: (2020)

Perfusion vector—a new method to quantify myocardial perfusion scintigraphy images: a simulation study with validation in patients
por: Minarik, David, et al.
Publicado: (2015)

Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [(18)F]-PSMA-1007 PET-CT
por: Trägårdh, Elin, et al.
Publicado: (2022)

Artificial Intelligence Increases the Agreement among Physicians Classifying Focal Skeleton/Bone Marrow Uptake in Hodgkin’s Lymphoma Patients Staged with [(18)F]FDG PET/CT—a Retrospective Study
por: Sadik, May, et al.
Publicado: (2022)

Prediction of Neoadjuvant Chemotherapy Response in Osteosarcoma Using Convolutional Neural Network of Tumor Center (18)F-FDG PET Images
por: Kim, Jingyu, et al.
Publicado: (2021)

Biokinetics and dosimetry of (18)F‐PSMA‐1007 in patients with prostate cancer
por: Hvittfeldt, Erland, et al.
Publicado: (2022)

(18)F-FDG PET/CT Findings in Cytomegalovirus Colitis
por: Kjaer, Anna Sophie L., et al.
Publicado: (2018)

PET probes beyond (18)F-FDG
por: Jiang, Lei, et al.
Publicado: (2014)

Measurement Repeatability of (18)F-FDG PET/CT Versus (18)F-FDG PET/MRI in Solid Tumors of the Pelvis
por: Fraum, Tyler J., et al.
Publicado: (2019)

Head-to-head comparison of a Si-photomultiplier-based and a conventional photomultiplier-based PET-CT system
por: Oddstig, Jenny, et al.
Publicado: (2021)

A convolutional neural network-based system to estimate the arterial plasma radioactivity curve in (18)F-FDG dynamic brain PET study
por: Kawauchi, Keisuke, et al.
Publicado: (2023)

18F-FDG PET/MRI and 18F-FDG PET/CT for the Management of Gynecological Malignancies: A Comprehensive Review of the Literature
por: Allahqoli, Leila, et al.
Publicado: (2023)

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR
por: Tian, Defeng, et al.
Publicado: (2022)

The sensitivity and specificity of (18)F-FDG PET/CT in spinal leptomeningeal metastases: the synergistic effect of the (18)F-FDG PET-CT to gadolinium-enhanced MRI
por: Luo, Zhe-Huang, et al.
Publicado: (2023)

(18)F-FDG PET/CT Imaging In Oncology
por: Almuhaideb, Ahmad, et al.
Publicado: (2011)

Motion frozen (18)F-FDG cardiac PET
por: Le Meunier, Ludovic, et al.
Publicado: (2010)

Scar Sarcoidosis on (18)F-FDG PET/CT
por: Arora, Saurabh, et al.
Publicado: (2019)

18F-FDG PET/CT and COVID-19
por: Joob, Beuy, et al.
Publicado: (2020)

[18F]FDG PET/MRI in rectal cancer
por: Crimì, Filippo, et al.
Publicado: (2021)

Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer
por: Borrelli, Pablo, et al.
Publicado: (2022)

Hypoxia is important in F-18 FDG accumulation in thecoma-fibroma tumors on F-18 FDG PET/CT scans
por: SEINO, HIROKO, et al.
Publicado: (2016)

Diagnostic performance of prospective same-day 18F-FDG PET/MRI and 18F-FDG PET/CT in the staging and response assessment of lymphoma
por: Mistry, Vijay, et al.
Publicado: (2023)

AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT
por: Gålne, Anni, et al.
Publicado: (2023)

(18)F-FDG-PET Imaging for Post-COVID-19 Brain and Skeletal Muscle Alterations
por: Rudroff, Thorsten, et al.
Publicado: (2021)

Crossed cerebellar diaschisis on F-18 FDG PET/CT
por: Agrawal, Kanhaiya Lal, et al.
Publicado: (2011)

Peritoneal Mouse as Detected on (18)F-FDG PET-CT
por: Allam, Talha, et al.
Publicado: (2013)

(18)F-FDG PET-CT for Staging of Conjunctival Melanoma
por: Damian, Andres, et al.
Publicado: (2013)

(18)F-FDG PET/CT in Pleural Epithelioid Hemangioendothelioma
por: Albano, Domenico, et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_carv1chq2lqrok0pdqfi55997g