Cargando…

Deep learning–based metal artefact reduction in PET/CT imaging

OBJECTIVES: The susceptibility of CT imaging to metallic objects gives rise to strong streak artefacts and skewed information about the attenuation medium around the metallic implants. This metal-induced artefact in CT images leads to inaccurate attenuation correction in PET/CT imaging. This study i...

Descripción completa

Detalles Bibliográficos
Autores principales:	Arabi, Hossein, Zaidi, Habib
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2021
Materias:	Physics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270868/ https://www.ncbi.nlm.nih.gov/pubmed/33569626 http://dx.doi.org/10.1007/s00330-021-07709-z

Ejemplares similares

Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging
por: Sanaat, Amirhossein, et al.
Publicado: (2021)

Artefacts of PET/CT images
por: Pettinato, C, et al.
Publicado: (2006)

Deep‐TOF‐PET: Deep learning‐guided generation of time‐of‐flight from non‐TOF brain PET images in the image and projection domains
por: Sanaat, Amirhossein, et al.
Publicado: (2022)

Motion artefact reduction in coronary CT angiography images with a deep learning method
por: Ren, Pengling, et al.
Publicado: (2022)

MRI‐guided attenuation correction in torso PET/MRI: Assessment of segmentation‐, atlas‐, and deep learning‐based approaches in the presence of outliers
por: Arabi, Hossein, et al.
Publicado: (2021)

Reduction of artefacts caused by hip implants in CT-based attenuation-corrected PET images using 2-D interpolation of a virtual sinogram on an irregular grid
por: Abdoli, Mehrsima, et al.
Publicado: (2011)

Quantitative Effect of Metal Artefact Reduction on CT-based attenuation correction in FDG PET/CT in patients with hip prosthesis
por: Haemels, Maarten, et al.
Publicado: (2021)

Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy
por: Arabi, Hossein, et al.
Publicado: (2020)

Direct inference of Patlak parametric images in whole-body PET/CT imaging using convolutional neural networks
por: Zaker, Neda, et al.
Publicado: (2022)

An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images
por: Boehringer, Andrew S., et al.
Publicado: (2023)

Robust-Deep: A Method for Increasing Brain Imaging Datasets to Improve Deep Learning Models’ Performance and Robustness
por: Sanaat, Amirhossein, et al.
Publicado: (2022)

Whole-body voxel-based internal dosimetry using deep learning
por: Akhavanallaf, Azadeh, et al.
Publicado: (2020)

Non-local mean denoising using multiple PET reconstructions
por: Arabi, Hossein, et al.
Publicado: (2020)

Metal artefact reduction for accurate tumour delineation in radiotherapy
por: Kovacs, David Gergely, et al.
Publicado: (2018)

The metal post material influences the performance of artefact reduction algorithms in CBCT images
por: Farias-Gomes, Amanda, et al.
Publicado: (2022)

Metal artifact reduction on cervical CT images by deep residual learning
por: Huang, Xia, et al.
Publicado: (2018)

Reduction of Artefacts in JPEG-XR Compressed Images
por: Hua, Kai-Lung, et al.
Publicado: (2019)

Differential privacy preserved federated transfer learning for multi-institutional (68)Ga-PET image artefact detection and disentanglement
por: Shiri, Isaac, et al.
Publicado: (2023)

CT radiation dose reduction in patients with total hip arthroplasties using model-based iterative reconstruction and orthopaedic metal artefact reduction
por: Wellenberg, Ruud H. H., et al.
Publicado: (2019)

COMPARISON OF METAL ARTEFACTS FOR DIFFERENT DUAL ENERGY CT TECHNIQUES
por: Pettersson, E, et al.
Publicado: (2021)

Deep learning-based fully automated Z-axis coverage range definition from scout scans to eliminate overscanning in chest CT imaging
por: Salimi, Yazdan, et al.
Publicado: (2021)

Completion of Metal-Damaged Traces Based on Deep Learning in Sinogram Domain for Metal Artifacts Reduction in CT Images
por: Zhu, Linlin, et al.
Publicado: (2021)

Localising ingested metallic foreign bodies to guide surgical planning: A novel use for the CT metal artefact reduction algorithm
por: Abernethy, Peter, et al.
Publicado: (2021)

Deep learning‐guided joint attenuation and scatter correction in multitracer neuroimaging studies
por: Arabi, Hossein, et al.
Publicado: (2020)

Impact of metal implants on xSPECT/CT Bone reconstruction: the “shining metal artefact”
por: Lima, Thiago V. M., et al.
Publicado: (2020)

Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
por: Aghakhan Olia, Narges, et al.
Publicado: (2021)

Comparison of Motion Artefact Reduction Methods and the Implementation of Adaptive Motion Artefact Reduction in Wearable Electrocardiogram Monitoring
por: An, Xiang, et al.
Publicado: (2020)

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning
por: Shiri, Isaac, et al.
Publicado: (2022)

Measuring femoral lesions despite CT metal artefacts: a cadaveric study
por: Malan, Daniel F., et al.
Publicado: (2011)

Assessment of metal implant induced artefacts using photon counting spectral CT
por: Amma, Maya Rajeswari, et al.
Publicado: (2019)

Simultaneous trimodal PET-MR-EEG imaging: Do EEG caps generate artefacts in PET images?
por: Rajkumar, Ravichandran, et al.
Publicado: (2017)

Metal artefact reduction of different alloys with dual energy computed tomography (DECT)
por: Vellarackal, Anand John, et al.
Publicado: (2021)

Use of single photon metal artefact reduction in the detection of an impacted capsule endoscope
por: Zhou, Kevin Z, et al.
Publicado: (2017)

Evaluating metallic artefact of biodegradable magnesium-based implants in magnetic resonance imaging
por: Espiritu, Jonathan, et al.
Publicado: (2022)

Compensating for visibility artefacts in photoacoustic imaging with a deep learning approach providing prediction uncertainties
por: Godefroy, Guillaume, et al.
Publicado: (2020)

Comparison and Combination of Dual-Energy- and Iterative-Based Metal Artefact Reduction on Hip Prosthesis and Dental Implants
por: Bongers, Malte N., et al.
Publicado: (2015)

Formation and reduction of streak artefacts in electron tomography
por: Cao, M, et al.
Publicado: (2010)

Archaeology of algorithmic artefacts
por: Link, David
Publicado: (2016)

The impact of a metal artefact reduction algorithm on treatment planning for patients undergoing radiotherapy of the pelvis
por: King, John, et al.
Publicado: (2022)

Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep neural network: a dual-center study
por: Salimi, Yazdan, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_8k5ek2p2fa7jbgi1t9q1d5ugkn