Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
565-03-010 Registered Abstract

Advancing Whole-Brain Ultra-High-Resolution fMRI at 7T Using Recurrent Inference Machines

Primary: Brain Function and fMRI - fMRI Acquisition
Secondary: Acquisition & Reconstruction - Image Reconstruction: AI
565-03-010 · Mesoscale Functional MRI and Acquisition Strategies · Wednesday, 13 May, 1:40 PM–2:35 PM · Digital Posters Row F
Keywords: Ultra-high resolution fMRI Head imaging at 7 Tesla Physics-informed Deep Learning FMRI 7T Spiral fMRI
Accepted
Mitra Tavakkoli 1, Filipe Ledo1, Chaoping Zhang2, Matthan W Caan3, Ravi Menon1
1Medical biophysics, Robarts Research Institute - Western University, Canada
2the Netherlands Cancer Institute, Amsterdam, Netherlands
3Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
Presenting Author: Mitra Tavakkoli

Synopsis

Motivation:
Goals:
Approach:
Hypothesis:
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. Kasper L, et al. "Advances in spiral fMRI: A high-resolution study with single-shot acquisition." NeuroImage 246 (2022): 118738.
2. Ledo F, et al. "Spiral Keyhole (SpiralK) Imaging: an in silico investigation." In Proceedings of the 32nd Annual Meeting of ISMRM. Hawaii; 2025.
3. Lustig M, et al. "Compressed sensing MRI." IEEE signal processing magazine 25.2 (2008): 72-82.
4. Tavakkoli M, et al. "A Review on Accelerated Magnetic Resonance Imaging Techniques: Parallel Imaging, Compressed Sensing, and Machine Learning." Critical Reviews™ in Biomedical Engineering(2025).
5. Lønning K, et al. "Dynamic recurrent inference machines for accelerated MRI-guided radiotherapy of the liver." Computerized Medical Imaging and Graphics 113 (2024): 102348.
6. Zhang Ch, et al. "Radial-rim: accelerated radial 4D MRI using the recurrent inference machine." In Proceedings of the 30th Annual Meeting of ISMRM. Toronto; 2023.
7. Tavakkoli M, et al. "Accelerating Free-Breathing Liver MRI at 7T using Recurrent Inference Machines." In Proceedings of the 32nd Annual Meeting of ISMRM. Hawaii; 2025.
8. Liebrand L., et al. "Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits." Magnetic Resonance Materials in Physics, Biology and Medicine 38.1 (2025): 1-12.
9. Ribeiro F, et al. "DeepRetinotopy: Predicting the Functional Organization of Human Visual Cortex from Structural MRI Data using Geometric Deep Learning." arXiv preprint arXiv:2005.12513 (2020).
10. Comby P, et al. "SNAKE-fMRI: A modular fMRI data simulator from the space-time domain to k-space and back." arXiv preprint arXiv:2404.08282 (2024).
11. Wang Z, et al. "Image quality assessment: from error visibility to structural similarity." IEEE transactions on image processing 13.4 (2004): 600-612.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/565-03-010