Deep learning reconstruction for cardiac magnetic resonance fingerprinting T 1 and T 2 mapping-Reference-Cited by-同舟云学术

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Deep learning reconstruction for cardiac magnetic resonance fingerprinting T 1 and T 2 mapping

Published:2020-10-26 Issue:4 Volume:85 Page:2127-2135
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magn. Reson. Med.

Author:

Hamilton Jesse I.¹^ORCID,Currey Danielle²,Rajagopalan Sanjay³⁴,Seiberlich Nicole¹^ORCID

Affiliation:

1. Department of Radiology University of Michigan Ann Arbor Michigan USA

2. Department of Computer Science Johns Hopkins University Baltimore Maryland USA

3. Department of Radiology University Hospitals Cleveland Medical Center Cleveland Ohio USA

4. Division of Cardiovascular Medicine University Hospitals Cleveland Medical Center Cleveland Ohio USA

Funder

Siemens Healthineers

National Heart, Lung, and Blood Institute

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.28568

Reference23 articles.

1. Quantitative evaluation of ischemic myocardial scar tissue by unenhanced T1 mapping using 3.0 Tesla MR scanner

2. T1 mapping in myocarditis – headway to a new era for cardiovascular magnetic resonance

3. T2 quantification for improved detection of myocardial edema

4. Magnetic resonance fingerprinting

5. MR fingerprinting for rapid quantification of myocardial T1, T2, and proton spin density

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1. Deep magnetic resonance fingerprinting based on Local and Global Vision Transformer;Medical Image Analysis;2024-07

2. Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging;Circulation: Cardiovascular Imaging;2024-06

3. The role of artificial intelligence in cardiovascular magnetic resonance imaging;Progress in Cardiovascular Diseases;2024-06

4. Sparsity Constrained Linear Tangent Space Alignment Model (LTSA) for 3d Cardiac Extracellular Volume Mapping;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

5. Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review;Bioengineering;2024-02-28

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