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PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction

Zimmermann Felix F., Kolbitsch Christoph, Schuenke Patrick, Kofler Andreas
Keywords:

Differentiable optimization, learned regularization, neural network, T1 -mapping, unrolled optimization, quantitative magnetic resonance imaging

Document type Article
Journal title / Source IEEE Transactions on Computational Imaging
Volume 10
Issue 1
Page numbers / Article number 628-639
Publisher's name Institute of Electrical and Electronics Engineers (IEEE)
Publisher's address (city only) Piscataway, NJ, United States
Publication date 2024
ISSN 2333-9403, 2334-0118, 2573-043
DOI 10.1109/TCI.2024.3388869
Language English

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Name of Call / Funding Programme
Metrology Partnership 2022: Health