Dataset

Developing Human Connectome Project spatio-temporal surface atlas of the fetal brain

Vycheslav Karolis¹, Logan Williams², Vanessa Kyriakopoulou¹, Jelena Bozek³, Alena Uus², Antonios Makropoulos⁴, Andreas Schuh⁵, Lucilio Cordero Grande¹, Emer Hughes¹, Anthony Price¹, Maria Deprez¹, Mary Rutherford¹, A. David Edwards¹, Daniel Rueckert⁶, Stephen Smith⁷, Joseph Hajnal², Tomoki Arichi¹, Emma Robinson²

¹Centre for the Developing Brain, King’s College London, London, UK
²School of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK
³University of Zagreb, Zagreb, Croatia
⁴ThinkSono, London, United Kingdom
⁵Department of Computing, Imperial College London, London, UK
⁶Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
⁷FMRIB, University of Oxford, Oxford, UK

DOI: 10.12751/g-node.qj5hs7 BROWSE REPOSITORY BROWSE ARCHIVE DOWNLOAD ARCHIVE (ZIP 300 MiB)

Published 17 May. 2023 | License Creative Commons CC0 1.0 Public Domain Dedication

Description

This repository contains spatio-temporal surface atlas, spanning 21-36 weeks of gestation, generated by adapting the procedure developed for the neonatal surface atlas in Bozek et al., 2018, which iteratively refines templates through a repeated alignment of individuals to a common space using MSM algorithm to the fetal data. At each iteration, the age-specific templates are obtained through weighted averaging of co-registered surfaces, whereby weights are defined by the Gaussians centred on the gestational weeks for which templates are calculated, and are subsequently used as a target space for the following iteration. Adaptive kernel regression, compensating for a difference in the number of scans available for different ages, was used to parameterise the width of the Gaussians. The atlas was generated in three stages: first, a common reference space was initialised via affine sulcal-depth-based registration to the dHCP neonatal GW36 template. At the next iteration, the template was refined using sulcal-depth-based nonlinear alignment, followed by 4 iterations of curvature-based alignment (a more fine-grained feature than the sulcal depth).

Keywords

References

J. Bozek, A. Makropoulos, A. Schuh, S. Fitzgibbon, R. Wright, M. F. Glasser, T. S. Coalson, J. O’Muircheartaigh, J. Hutter, A. N. Price, L. Cordero-Grande, R. P. A. G. Teixeira, E. Hughes, N. Tusor, K. P. Baruteau, M. A. Rutherford, A. D. Edwards, J. V. Hajnal, S. M. Smith, D. Rueckert, M. Jenkinson, E. C. Robinson. (2018). Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project. NeuroImage. 179, 11–29. https://doi.org/10.1016/j.neuroimage.2018.06.018

Funding

European Union's Seventh Framework Programme (FP/2007-2013) 319456

Citation

Karolis V, Williams L, Kyriakopoulou V, Bozek J, Uus A, Makropoulos A, Schuh A, Cordero Grande L, Hughes E, Price A, Deprez M, Rutherford M, Edwards AD, Rueckert D, Smith S, Hajnal J, Arichi T, Robinson E (2023) Developing Human Connectome Project spatio-temporal surface atlas of the fetal brain. G-Node. https://doi.org/10.12751/g-node.qj5hs7