Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning-Reference-Cited by-同舟云学术

Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning

Published:2020-03-13 Issue:4 Volume:84 Page:2204-2218
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magn Reson Med

Author:

Berhane Haben¹^ORCID,Scott Michael²³^ORCID,Elbaz Mohammed²³,Jarvis Kelly³^ORCID,McCarthy Patrick⁴,Carr James²,Malaisrie Chris³,Avery Ryan³^ORCID,Barker Alex J.⁵,Robinson Joshua D.¹,Rigsby Cynthia K.¹,Markl Michael²³

Affiliation:

1. Department of Medical Imaging Ann & Robert H. Lurie Children’s Hospital of Chicago Chicago Illinois

2. Department of Biomedical Engineering Northwestern University Chicago Illinois

3. Department of Radiology Northwestern University Chicago Illinois

4. Divison of Cardiac Surgery Northwestern University Chicago Illinois

5. Anschutz Medical Campus University of Colorado Aurora Colorado

Funder

National Heart, Lung, and Blood Institute

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.28257

Reference29 articles.

1. Evaluation of aortic stenosis by cardiovascular magnetic resonance imaging: comparison with established routine clinical techniques

2. Aortic Regurgitation Quantification Using Cardiovascular Magnetic Resonance

3. MRI and MRA of Aortic Disease

4. 4D Flow MRI Applications for Aortic Disease

5. The Role of Imaging of Flow Patterns by 4D Flow MRI in Aortic Stenosis

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