Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-04-010 ISMRM Abstract

Optimization of Acquisition Parameters in Sonic DL–Accelerated LAVA-FLEX: Effects of Slice Partial Fourier and Z-Resolution

Primary: Body - Liver
Secondary: Acquisition & Reconstruction - Image Reconstruction: AI
365-04-010 · Body MR: Potpourri of Techniques in Uterine, Cervical, Liver, and Kidney Imaging · Monday, 11 May, 2:45 PM–3:40 PM · Digital Posters Row F
Keywords: Liver Deep learning reconstruction 3D T1-weighted imaging Rapid imaging MRI sequence optimization
Accepted
Junya Tsuzaki 1, Manabu Arai1, Tetsushi Habe2, Shotaro Fuchibe3, Ty A Cashen4, Xucheng Zhu5, Manabu Hase1, Sari Motomatsu2, Yoshinobu Nunokawa2, Yoshitake Yamada1, Masahiro Jinzaki1
1Department of Radiology, Keio University School of Medicine, Tokyo, Japan
2Office of Radiation Technology, Keio University Hospital, Tokyo, Japan
3Science and Technology Organization, GE HealthCare, Hino, Japan
4GE HealthCare, San Ramon, United States of America
5GE HealthCare Global MR Applications & Workflow, Menlo Park, United States of America
Presenting Author: Junya Tsuzaki

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. Eyre K, Rafiee MJ, Leo M, Ma J, Hillier E, Amini N, 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]
2. Ma J, Zhu X, Kaushik S, Ali E, Li L, Manickam K, et al. Qualitative and quantitative evaluation of a deep learning-based reconstruction for accelerated cardiac cine imaging. Bioengineering (Basel). 2025;12(3):231. doi:10.3390/bioengineering12030231 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-04-010