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Deep learning phase error correction for cerebrovascular 4D flow MRI

Scientific reports, 2023-06, Vol.13 (1), p.9095-9095, Article 9095

2023

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Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging

Journal of thoracic imaging, 2019-05, Vol.34 (3), p.192

2019

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Optimizing the diagnosis and assessment of chronic thromboembolic pulmonary hypertension with advancing imaging modalities

Pulmonary Circulation, 2021-04, Vol.11 (2), p.1-12

2021

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Quantification of hemodynamics of cerebral arteriovenous malformations after stereotactic radiosurgery using 4D flow magnetic resonance imaging

Journal of magnetic resonance imaging, 2021-06, Vol.53 (6), p.1841-1850

2021

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Beyond the AJR : Potential of Deep Learning Image Classification for Chest Radiography

American journal of roentgenology (1976), 2022-04, Vol.218 (4), p.762

Hsiao, Albert

2022

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Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI

Radiology, 2022-03, Vol.302 (3), p.584-592

2022

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Deep Learning-based Prescription of Cardiac MRI Planes

Radiology. Artificial intelligence, 2019-11, Vol.1 (6), p.e180069-e180069

2019

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Robust 4D flow denoising using divergence-free wavelet transform

Magnetic resonance in medicine, 2015-02, Vol.73 (2), p.828-842

2015

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Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach

Scientific reports, 2022-01, Vol.12 (1), p.786-786, Article 786

2022

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A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot

Journal of cardiovascular magnetic resonance, 2023-02, Vol.25 (1), p.15-15, Article 15

2023

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Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN's Learned Features

IEEE access, 2023, Vol.11, p.5144-5160

2023

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Cloud-processed 4D CMR flow imaging for pulmonary flow quantification

European journal of radiology, 2016-10, Vol.85 (10), p.1849-1856

2016

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Mitral Valve Prolapse—The Role of Cardiac Imaging Modalities

Structural heart (Online), 2022-06, Vol.6 (2), p.100024-100024, Article 100024

2022

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4D Flow Vorticity Visualization Predicts Regions of Quantitative Flow Inconsistency for Optimal Blood Flow Measurement

Radiology. Cardiothoracic imaging, 2020-02, Vol.2 (1), p.e190054

2020

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Deep Learning Radiographic Assessment of Pulmonary Edema: Optimizing Clinical Performance, Training With Serum Biomarkers

IEEE access, 2022, Vol.10, p.48577-48588

2022

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Deep Learning Single-Frame and Multiframe Super-Resolution for Cardiac MRI

Radiology, 2020-06, Vol.295 (3), p.552-561

2020

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Challenges and Opportunities in Medical Artificial Intelligence

APSIPA transactions on signal and information processing, 2023-01, Vol.12 (5)

2023

Volltextzugriff (PDF)

Deep Learning Localization of Pneumonia: 2019 Coronavirus (COVID-19) Outbreak

Journal of thoracic imaging, 2020-05, Vol.35 (3), p.W87

2020

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Thrombin receptor and RhoA mediate cell proliferation through integrins and cysteine-rich protein 61

The FASEB journal, 2008-11, Vol.22 (11), p.4011-4021

2008

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Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

European radiology experimental, 2019-10, Vol.3 (1), p.43-14, Article 43

2019

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4D Flow Cardiac Magnetic Resonance Uncovers the Cause of Bioprosthetic Pulmonary Valve Dysfunction

JACC. Case reports, 2019-12, Vol.1 (4), p.485-486

2019

Volltextzugriff (PDF)

Cardiac MRI Field Strength: Counterpoint-Image Quality Gains From Higher SNR Are Achievable at 3 T

American journal of roentgenology (1976), 2024-03, Vol.222 (3), p.e2330071

2024

Volltextzugriff (PDF)

Congenital heart disease assessment with 4D flow MRI

Journal of magnetic resonance imaging, 2015-10, Vol.42 (4), p.870-886

2015

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Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI‐NET)

Magnetic resonance in medicine, 2019-05, Vol.81 (5), p.3283-3291

2019

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Improved visualization and quantification of 4D flow data using divergence-free wavelets

Journal of cardiovascular magnetic resonance, 2013-01, Vol.15 (Suppl 1), p.E26-E26, Article E26

2013

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Deep learning phase error correction for cerebrovascular 4D flow MRI

Machine Learning and Deep Neural Networks in Thoracic and Cardiovascular Imaging

Optimizing the diagnosis and assessment of chronic thromboembolic pulmonary hypertension with advancing imaging modalities

Quantification of hemodynamics of cerebral arteriovenous malformations after stereotactic radiosurgery using 4D flow magnetic resonance imaging

Beyond the AJR : Potential of Deep Learning Image Classification for Chest Radiography

Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI

Deep Learning-based Prescription of Cardiac MRI Planes

Robust 4D flow denoising using divergence-free wavelet transform

Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach

A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot

Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN's Learned Features

Cloud-processed 4D CMR flow imaging for pulmonary flow quantification

Mitral Valve Prolapse—The Role of Cardiac Imaging Modalities

4D Flow Vorticity Visualization Predicts Regions of Quantitative Flow Inconsistency for Optimal Blood Flow Measurement

Deep Learning Radiographic Assessment of Pulmonary Edema: Optimizing Clinical Performance, Training With Serum Biomarkers

Deep Learning Single-Frame and Multiframe Super-Resolution for Cardiac MRI

Challenges and Opportunities in Medical Artificial Intelligence

Deep Learning Localization of Pneumonia: 2019 Coronavirus (COVID-19) Outbreak

Thrombin receptor and RhoA mediate cell proliferation through integrins and cysteine-rich protein 61

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

4D Flow Cardiac Magnetic Resonance Uncovers the Cause of Bioprosthetic Pulmonary Valve Dysfunction

Cardiac MRI Field Strength: Counterpoint-Image Quality Gains From Higher SNR Are Achievable at 3 T

Congenital heart disease assessment with 4D flow MRI

Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI‐NET)

Improved visualization and quantification of 4D flow data using divergence-free wavelets

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