Dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain

<p>This dataset gathers synthetic-yet-highly-realistic T2-weighted magnetic resonance images (MRI) of the fetal brain based on the latest development of our prototype Fetal Brain magnetic resonance Acquisition Numerical phantom that now simulates local heterogeneities within white matter tissues throughout maturation (FaBiAN v2.0).<br>This dataset is associated with the following paper:</p> <p><strong>- Lajous H. et al. (2024) A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain.</strong> Submitted to Nature Scientific Data, Pre-print available https://doi.org/10.1101/2024.04.08.588566</p> <p>We propose this unique, extensive fetal MRI dataset of simulated standard clinical fast spin echo sequences in both healthy and pathological neurodevelopmental trajectories to address data scarcity in this sensitive population, and therefore support the continuous endeavor of the community to develop advanced post-processing methods as well as cutting-edge artificial intelligence models. Automated brain tissue annotations of the two-dimensional, low-resolution series as well as super-resolution (SR) reconstructions of the fetal brain volumes are also included.</p> <p><strong>Work using any of these data should cite the following references:</strong></p> <ul> <li>Lajous, H. et al. A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain. Submitted to Nature Scientific Data (2024), https://doi.org/10.1101/2024.04.08.588566</li> <li>Lajous, H. et al. Dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain. Zenodo (2024). 10.5281/zenodo.10940427</li> <li>Lajous, H., le Boeuf Fl&oacute;, A., Esteban, O. &amp; Bach Cuadra, M. Medical-Image-Analysis-Laboratory/FaBiAN: FaBiAN v2.0 (2.0). Zenodo (2023), 10.5281/zenodo.5471094</li> </ul> <p>This work was supported by the Swiss National Science Foundation through grant 182602, and by the ProTechno Foundation. We acknowledge access to the facilities and expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Ecole Polytechnique F&eacute;d&eacute;rale de Lausanne (EPFL), University of Geneva (UNIGE) and Geneva University Hospitals (HUG).</p> <p>Medical Image Analysis Laboratory - Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland &amp; CIBM Center for Biomedical Imaging. 2024.</p> <p>Note:&nbsp;<em>Terms of use for the original cohort (</em>Fidon, L., Aertsen, M., Emam, D., et al. Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation. MICCAI, 2021<em>) are for research and education purposes only.</em></p>