A framework based on sulcal constraints to align preterm, infant and adult human brain images acquired in vivo and post mortem

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Abstract
Robust spatial alignment of post mortem data and in vivo MRI acquisitions from different ages, especially from the early developmental stages, into standard spaces is still a bottleneck hampering easy comparison with the mainstream neuroimaging results. In this paper, we test a landmark-based spatial normalization strategy as a framework for the seamless integration of any macroscopic dataset in the context of the Human Brain Project (HBP). This strategy stems from an approach called DISCO embedding sulcal constraints in a registration framework used to initialize DARTEL, the widely used spatial normalization approach proposed in the SPM software. We show that this strategy is efficient with a heterogeneous dataset including challenging data as preterm newborns, infants, post mortem histological data and a synthetic atlas computed from averaging the ICBM database, as well as more commonly studied data acquired in vivo in adults. We then describe some perspectives for a research program aiming at improving folding pattern matching for atlas inference in the context of the future HBP’s portal.
Funding Information
  • Horizon 2020 Framework Programme (785907, 720270, 604102)
  • Fondation de France
  • Fondation Fyssen (FR)
  • Swiss National Science Foundation
  • Leenards Foundation
  • European consortium NEOBRAIN

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