2766 ISMRM Abstract

Accelerated FLAIR imaging at 0.6T using T2W-guided multi-contrast deep learning-based reconstruction using a Zero-Shot approach

2766 · AI-Based Acquisition & Reconstruction: Part II · Tuesday, 13 May, 2:30 PM–3:30 PM · Exhibition Hall

Keywords: Brain AI/ML Image Reconstruction Image Reconstruction Low-Field MRI Machine Learning/Artificial Intelligence

Accepted

Navid Jabarimani ^1,2, Chinmay Rao², Ece Ercan³, Yiming Dong¹, Nicola Pezzotti⁴, Mariya Doneva⁵, Matthias van Osch¹, Marius Staring², Martijn Nagtegaal¹

¹C.J. Gorter MRI Center, Radiology, Leiden University Medical Center, Leiden, Netherlands

²Division of Image Processing, Radiology, Leiden University Medical Center, Leiden, Netherlands

³MR Clinical Science, Best, Netherlands

⁴Philips Cardiologs, Paris, France

⁵Philips Innovative Technologies, Hamburg, Germany

Presenting Author: Navid Jabarimani

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 2025 ISMRM and 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.

References

1. Campbell-Washburn, A. E. et al. Opportunities in Interventional and Diagnostic Imaging by Using High-Performance Low-Field-Strength MRI. Radiology 293, 384-393 (2019).

2. Arnold, T. C., Freeman, C. W., Litt, B. & Stein, J. M. Low-field MRI: Clinical promise and challenges. J Magn Reson Imaging 57, 25-44 (2023).

3. Lavrova, A. et al. Quality assessment of routine brain imaging at 0.55 T: initial experience in a clinical workflow. NMR in Biomedicine 37, e5017 (2024).

4. Rao, C. et al. A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling. arXiv preprint arXiv:2409.13477 (2024).

Cite this abstract

http://echo.ismrm.org/p/ISMRM2025/2766