Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
461-01-014 ISMRM Abstract

Deep Learning–Accelerated MOLLI T1 Mapping with Variable-Density Undersampling

Primary: Cardiovascular
Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
461-01-014 · Cardiac Tissue Characterization · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row B
Keywords: Deep learning MOLLI T1 Variable-density sampling
Accepted
Junjie Ma1, Gaspar Delso2, Haonan Wang1, Sagar Mandava3, Xucheng Zhu4, Fara Nikbeh4, Dan W Rettmann5, Michael Carl1, Martin A Janich 6
1GE HealthCare, San Ramon, United States of America
2GE HealthCare, Madrid, Spain
3GE HealthCare (Atlanta, USA), United States of America
4GE HealthCare (Menlo Park, US), Menlo Park, United States of America
5GE HealthCare, Rochester, United States of America
6GE Healthcare, Munich, Germany
Presenting Author: Martin A Janich

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Philip H, Pankaj G, Daniel RM, David AB, John PG, Sven P. Cardiac T1 Mapping and Extracellular Volume (ECV) in clinical practice: A comprehensive review. J Cardiovasc Magn Reson. 2017;18(1):89. doi: 10.1186/s12968-016-0308-4. [doi]
2. Valentina OP, Elif P, Y. C, Eike N. T1 Mapping in Characterizing Myocardial Disease: A Comprehensive Review. Circ Res. 2016;119(2):277-99. doi: 10.1161/CIRCRESAHA.116.307974. [doi]
3. Daniel RM, James CM, Vanessa MR, et al. Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI). J Cardiovasc Magn Reason. 2017;19(1):75. doi: 10.1186/s12968-017-0389-8. [doi]
4. Katerina E, Moezedin JR, Margherita L, et al. Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction. J Cardiovasc Magn Reson. 2024;26(2):101069. doi: 10.1016/j.jocmr.2024.101069. [doi]
5. Junjie M, Xucheng Z, Suryanarayanan K, et al. Qualitative and quantitative evaluation of a deep learning-based reconstruction for accelerated cardiac cine imaging. Bioengineering. 2025;12(3):231. doi: 10.3390/bioengineering12030231. [doi]
6. Junjie M, Michael V, Xucheng Z, et al. Optimization of variable-density undersampling for accelerated myocardial delayed enhancement imaging with deep learning reconstruction. ISMRM 2024. #1666.
7. Gamito MN and Steve CM. Accurate multidimensional Poisson-disk sampling. ACM Transactions on Graphics. 2009;29(1):19.
8. Ahn, Sangtae, et al. "Deep learning-based reconstruction of highly accelerated 3D MRI." arXiv preprint arXiv:2203.04674 (2022). https://doi.org/10.48550/arXiv.2203.04674. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/461-01-014