568-05-010 ISMRM Abstract

Improving the Precision and Repeatability of 0.55T Lung MRF Using a Deep Image Prior with Ensemble Averaging

Primary: Acquisition & Reconstruction - Quantitative Imaging: chest, abdomen, and pelvis

Secondary: Body - Lung

568-05-010 · Image Reconstruction I · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row I

Keywords: Lung MRI 0.55T Magnetic Resoance Fingerprinting Deep Image Prior T1 and T2 mapping

Accepted

Zexuan Liu ¹, Zhongnan Liu², Calder D Sheagren³, Gastao Cruz³, Nicole Seiberlich^3,4,5, Jesse Hamilton^3,4,5

¹Biomedical Engineering, University of Michigan, Ann Arbor, United States of America

²Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States of America

³Department of Radiology, University of Michigan, Ann Arbor, United States of America

⁴Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America

⁵University of Michigan, Ann Arbor, United States of America

Presenting Author: Zexuan Liu

Synopsis

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References

1. Campbell-Washburn AE, Ramasawmy R, Restivo MC, et al. Opportunities in Interventional and Diagnostic Imaging by Using High-Performance Low-Field-Strength MRI. Radiology. 2019;293(2):384-393. doi:10.1148/radiol.2019190452 [doi]

2. Liu Z, Lugogo N, Agarwal P, Hamilton J. Feasibility of Lung MR Fingerprinting at 0.55T using a Deep image Prior Reconstruction. In: Proc ISMRM: 2024.

3. Hamilton JI. A self-supervised deep learning reconstruction for shortening the breathhold and acquisition window in cardiac magnetic resonance fingerprinting. Front Cardiovasc Med. 2022;9:928546. doi:10.3389/fcvm.2022.928546 [doi]

4. Jiang Y, Ma D, Seiberlich N, Gulani V, Griswold MA. MR Fingerprinting Using Fast Imaging with Steady State Precession (FISP) with Spiral Readout. Magn Reson Med. 2015;74(6):1621-1631. doi:10.1002/mrm.25559 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/568-05-010