Cargando…

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software

PURPOSE: A novel phantom‐imaging platform, a set of software tools, for automated and high‐precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. METHODS: Th...

Descripción completa

Detalles Bibliográficos
Autores principales:	Markiewicz, Pawel J., da Costa‐Luis, Casper, Dickson, J., Barnes, A., Krokos, G., MacKewn, J., Clark, T., Wimberley, C., MacNaught, G., Yaqub, M. M., Gispert, J. D., Hutton, B. F., Marsden, P., Hammers, A., Reader, A. J., Ourselin, S., Herholz, K., Matthews, J. C., Barkhof, F.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2022
Materias:	QUANTITATIVE IMAGING AND IMAGE PROCESSING
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289925/ https://www.ncbi.nlm.nih.gov/pubmed/35271742 http://dx.doi.org/10.1002/mp.15596

Ejemplares similares

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis
por: Markiewicz, Pawel J., et al.
Publicado: (2017)

A review of PET attenuation correction methods for PET-MR
por: Krokos, Georgios, et al.
Publicado: (2023)

Intercomparison of MR‐informed PET image reconstruction methods
por: Bland, James, et al.
Publicado: (2019)

NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data
por: Jiao, Jieqing, et al.
Publicado: (2023)

Impact of PET/CT system, reconstruction protocol, data analysis method, and repositioning on PET/CT precision: An experimental evaluation using an oncology and brain phantom
por: Mansor, Syahir, et al.
Publicado: (2017)

A CT‐less approach to quantitative PET imaging using the LSO intrinsic radiation for long‐axial FOV PET scanners
por: Teimoorisichani, Mohammadreza, et al.
Publicado: (2021)

Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach
por: Beichel, Reinhard R., et al.
Publicado: (2016)

Repeatability of (18)F‐FDG PET radiomic features: A phantom study to explore sensitivity to image reconstruction settings, noise, and delineation method
por: Pfaehler, Elisabeth, et al.
Publicado: (2018)

Fast dynamic brain PET imaging using stochastic variational prediction for recurrent frame generation
por: Sanaat, Amirhossein, et al.
Publicado: (2021)

Comparison of DCE‐MRI kinetic parameters and FMISO‐PET uptake parameters in head and neck cancer patients
por: Simoncic, Urban, et al.
Publicado: (2017)

Plausibility and redundancy analysis to select FDG‐PET textural features in non‐small cell lung cancer
por: Pfaehler, Elisabeth, et al.
Publicado: (2021)

The impact of MR‐based attenuation correction in spinal cord FDG‐PET/MR imaging for neurological studies
por: Brancato, Valentina, et al.
Publicado: (2021)

Toward a standard for the evaluation of PET‐Auto‐Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation
por: Berthon, Beatrice, et al.
Publicado: (2017)

A data‐driven respiratory motion estimation approach for PET based on time‐of‐flight weighted positron emission particle tracking
por: Tumpa, Tasmia Rahman, et al.
Publicado: (2020)

(18)F‐fluoromisonidazole uptake in advanced stage non‐small cell lung cancer: A voxel‐by‐voxel PET kinetics study
por: McGowan, Daniel R., et al.
Publicado: (2017)

Synergistic impact of motion and acquisition/reconstruction parameters on (18)F‐FDG PET radiomic features in non‐small cell lung cancer: Phantom and clinical studies
por: Hosseini, Seyyed Ali, et al.
Publicado: (2022)

PET/MRI in Oncological Imaging: State of the Art
por: Bashir, Usman, et al.
Publicado: (2015)

Electromagnetic tracking in image‐guided laparoscopic surgery: Comparison with optical tracking and feasibility study of a combined laparoscope and laparoscopic ultrasound system
por: Xiao, Guofang, et al.
Publicado: (2018)

Lymphocytic Gastritis Identified by Abnormal PET Scan
por: Murphy, Christopher J., et al.
Publicado: (2017)

Early prediction of treatment response in rheumatoid arthritis by quantitative macrophage PET
por: Verweij, Nicki, et al.
Publicado: (2022)

Comparison of an in‐house hybrid DIR method to NiftyReg on CBCT and CT images for head and neck cancer
por: Jiang, Chunling, et al.
Publicado: (2022)

Effect of reconstruction methods and x-ray tube current–time product on nodule detection in an anthropomorphic thorax phantom: A crossed-modality JAFROC observer study
por: Thompson, J. D., et al.
Publicado: (2016)

Fully automated quantification method (FQM) of coronary calcium in an anthropomorphic phantom
por: van Praagh, Gijs D., et al.
Publicado: (2021)

Automatic quantitative analysis of pulmonary vascular morphology in CT images
por: Zhai, Zhiwei, et al.
Publicado: (2019)

Deep convolutional neural networks for multiplanar lung nodule detection: Improvement in small nodule identification
por: Zheng, Sunyi, et al.
Publicado: (2020)

Breast MRI segmentation for density estimation: Do different methods give the same results and how much do differences matter?
por: Doran, Simon J., et al.
Publicado: (2017)

A new 2D‐3D registration gold‐standard dataset for the hip joint based on uncertainty modeling
por: D'Isidoro, Fabio, et al.
Publicado: (2021)

Deep learning‐based carotid media‐adventitia and lumen‐intima boundary segmentation from three‐dimensional ultrasound images
por: Zhou, Ran, et al.
Publicado: (2019)

SAUN: Stack attention U‐Net for left ventricle segmentation from cardiac cine magnetic resonance imaging
por: Sun, Xiaowu, et al.
Publicado: (2021)

AI for PET image reconstruction
por: Reader, Andrew J, et al.
Publicado: (2023)

Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features
por: Lo, P., et al.
Publicado: (2016)

Fully automated segmentation of the left atrium, pulmonary veins, and left atrial appendage from magnetic resonance angiography by joint‐atlas‐optimization
por: Qiao, Menyun, et al.
Publicado: (2019)

Bridging the gap between prostate radiology and pathology through machine learning
por: Bhattacharya, Indrani, et al.
Publicado: (2022)

Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging
por: Seetharaman, Arun, et al.
Publicado: (2021)

Quantifying ventilation change due to radiation therapy using 4DCT Jacobian calculations
por: Patton, Taylor J., et al.
Publicado: (2018)

Prediction of transient tumor enlargement using MRI tumor texture after radiosurgery on vestibular schwannoma
por: Langenhuizen, Patrick P. J. H., et al.
Publicado: (2020)

Multiparametric deep learning tissue signatures for a radiological biomarker of breast cancer: Preliminary results
por: Parekh, Vishwa S., et al.
Publicado: (2019)

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas
por: Korfiatis, Panagiotis, et al.
Publicado: (2016)

Implementation and prospective clinical validation of AI‐based planning and shimming techniques in cardiac MRI
por: Edalati, Masoud, et al.
Publicado: (2021)

Feasibility of imaging (90)Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning
por: Kunnen, Britt, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_ser8fkifdhktke42hdu4bipkgi