Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
302-03-009 / 271-01-065 ISMRM Abstract

AI-guided autonomous fetal MRI

Primary: Acquisition & Reconstruction - AI methods
Secondary: Pediatrics - Fetal
302-03-009 · Next-Level Pediatric MRI: Technical Advances To Image Children Better · Monday, 11 May, 1:50 PM–3:40 PM · Hall 1B
271-01-065 · ISMRM AMPC Selected Posters · Sunday, 10 May, 7:00 AM–2:00 PM · Traditional Posters
Keywords: Real-time MRI Fetal MRI Deep Learning Segmentation Self-navigation
Accepted
Sara Neves Silva 1,2, Jordina Aviles Verdera1,2,3, Alena Uus1,2, Aysha Luis1, Susanne Schulz-Heise4, Sarah McElroy2,5, Raphael Tomi-Tricot2,5, Lisa Story1,6, Jo V Hajnal1,2, MARY A RUTHERFORD1,2, Jana Hutter1,2,3,7
1Early Life Imaging Research Department, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
2Imaging Physics and Engineering Department, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
3Smart Imaging Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
4Institute of Radiology, Uniklinikum Erlangen, Erlangen, Germany
5MR Research Collaborations, Siemens Healthcare Ltd., Camberly, United Kingdom
6Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom
7Smart Imaging Lab, Radiological Institute, University Hospital Erlangen (UKER), Erlangen, Germany
Presenting Author: Sara Neves Silva

Synopsis

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References

1. Neves Silva S, McElroy S, Aviles Verdera J, Colford K, St Clair K, Tomi-Tricot R, et al. Fully automated planning for anatomical fetal brain MRI on 0.55T. Magn Reson Med. 2024 Sep;92(3):1263–76.
2. Singh A, Salehi SSM, Gholipour A. Deep predictive motion tracking in magnetic resonance imaging: Application to fetal imaging. IEEE Trans Med Imaging. 2020 Nov;39(11):3523–34.
3. Gagoski B, Xu J, Wighton P, Tisdall MD, Frost R, Lo WC, et al. Automated detection and reacquisition of motion-degraded images in fetal HASTE imaging at 3 T. Magn Reson Med. 2022 Apr;87(4):1914–22.
4. Chow K, Kellman P, Xue H. Prototyping image reconstruction and analysis with FIRE. In: Proceedings of the SCMR 24th Annual Scientific Sessions, Virtual Meeting. 2021.
5. Uus A, Neves Silva S, Aviles Verdera J, Payette K, Hall M, Colford K, et al. Scanner-based real-time three-dimensional brain + body slice-to-volume reconstruction for T2-weighted 0.55-T low-field fetal magnetic resonance imaging. Pediatr Radiol. 2025 Mar;55(3):556–69.
6. Neves Silva S, Uus A, Waheed H, Bansal S, St Clair K, Norman W, et al. Scanner-based real-time automated volumetry reporting of the fetus, amniotic fluid, placenta, and umbilical cord for fetal MRI at 0.55T. Magn Reson Med [Internet]. 2025 Sep 24;(mrm.70097). Available from: http://dx.doi.org/10.1002/mrm.70097 [doi]
7. Aviles Verdera J, Neves Silva S, Payette KM, Tomi-Tricot R, Hall M, Story L, et al. Real-time fetal brain and placental T2* mapping at 0.55T MRI. Magn Reson Med. 2025 Aug;94(2):615–24.
8. Verdera JA, Bortolazzi A, Silva SN, Payette K, Clair KS, McElroy S, et al. HERON: High-Efficiency Real-Time mOtion quantification and re-acquisitioN for Fetal diffusion MRI. IEEE Trans Med Imaging [Internet]. 2025 May 14;PP. Available from: http://dx.doi.org/10.1109/TMI.2025.3569853 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/302-03-009