PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction
Zimmermann Felix F., Kolbitsch Christoph, Schuenke Patrick, Kofler AndreasDifferentiable 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 |