Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
403-02-003 ISMRM Abstract

Generalization of Synthetic CT from Diagnostic Spine MRI: A Multi-Center Approach

Primary: Analysis Methods - Image Synthesis and Translation
Secondary: Musculoskeletal - Bone
403-02-003 · AI-Enabled Image Synthesis and Translation · Tuesday, 12 May, 1:40 PM–3:30 PM · Auditorium 1
Keywords: Deep learning Synthetic CT Multi-center Spine Generalization
Accepted
Ryan Pollitt 1, Tom P. C Schlösser2, Lambertus W Bartels1, Marijn van Stralen3, Peter R Seevinck1,3
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
2Department of Orthopaedics, University Medical Center Utrecht, Utrecht, Netherlands
3MRIguidance B.V., Utrecht, Netherlands
Presenting Author: Ryan Pollitt

Synopsis

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References

1. Nijskens, L., van den Berg, C. A. T., Verhoeff, J. J. C., & Maspero, M. (2023). Exploring contrast generalisation in deep learning-based brain MRI-to-CT synthesis. Physica Medica, 112, 102642. https://doi.org/10.1016/j.ejmp.2023.102642 [doi]
2. Fetty, L., Löfstedt, T., Heilemann, G., Furtado, H., Nesvacil, N., Nyholm, T., Georg, D., & Kuess, P. (2020). Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion. Physics in Medicine & Biology, 65(10), 105004. https://doi.org/10.1088/1361-6560/ab857b [doi]
3. Florkow, M. C., Zijlstra, F., Willemsen, K., Maspero, M., van den Berg, C. A. T., Kerkmeijer, L. G. W., Castelein, R. M., Weinans, H., Viergever, M. A., van Stralen, M., & Seevinck, P. R. (2020). Deep learning–based MR‐to‐CT synthesis: The influence of varying gradient echo–based MR images as input channels. Magnetic Resonance in Medicine, 83(4), 1429–1441. https://doi.org/10.1002/mrm.28008 [doi]
4. Payer, C., Stern, D., Bischof, H., & Urschler, M. (2020). Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net.: 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. VISAPP, 124–133. https://doi.org/10.5220/0008975201240133 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/403-02-003