Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
562-04-011 ISMRM Abstract

Large sample evaluation of AI accelerated Clinical Pediatric Neuroimaging

Primary: Pediatrics - Neuro
Secondary: Acquisition & Reconstruction - Image Reconstruction: AI
562-04-011 · AI/DL in Pediatrics · Wednesday, 13 May, 2:35 PM–3:30 PM · Digital Posters Row C
Keywords: Deep learning reconstruction Pediatric brain MRI AI-Accelerated MRI Statistical analysis Paediatric epilepsy
Accepted
Karen J Kettless1, Camilla D Hansen2,3, Llucia Coll4, Marcel D Nickel5, Adam. E Hansen6, Melanie Ganz 7,8
1Siemens Healthcare A/S, Ballerup, Denmark
2Radiography Education, Copenhagen University College, Copenhagen, Denmark, Hvidovre, Denmark
3Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Copenhagen, Denmark
4Neurobiology Research Unit, Copenhagen, Denmark
5Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
6Dept. of Radiology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
7Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
8Neurobiology Research Unit, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
Presenting Author: Melanie Ganz

Synopsis

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References

1. Gallo-Bernal, S., Bedoya, M. A., Gee, M. S., & Jaimes, C. (2023). Pediatric magnetic resonance imaging: faster is better. Pediatric Radiology, 53(7), 1270-1284.
2. McGeown, T., Cleary, J. O., Kafiabadi, S., Adroja, N., Mellor, N., Moon, T., ... & Shah, S. Impact of AI Acceleration on Image Quality and Diagnostic Quality in Clinical Paediatric Neuroimaging. Proceedings of ISMRM 2025.
3. Anonymous. A dataset of clinical pediatric brain MRI with and without motion correction. In review at Scientific Data
4. Wei, H., Yoon, J. H., Jeon, S. K., Choi, J. W., Lee, J., Kim, J. H., ... & Lee, J. M. (2024). Enhancing gadoxetic acid–enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques. European Radiology, 34(10), 6712-6725.
5. Marchetto, E., Eichhorn, H., Gallichan, D., Schnabel, J. A., & Ganz, M. (2025). Agreement of image quality metrics with radiological evaluation in the presence of motion artifacts. Magnetic Resonance Materials in Physics, Biology and Medicine, 1-12.
6. Sullivan, G. M., & Artino Jr, A. R. (2013). Analyzing and interpreting data from Likert-type scales. Journal of graduate medical education, 5(4), 541.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/562-04-011