# Metadata for DOI registration according to DataCite Metadata Schema 4.1.
# For detailed schema description see https://doi.org/10.5438/0014

## Required fields

# The main researchers involved. Include digital identifier (e.g., ORCID)
# if possible, including the prefix to indicate its type.
authors:
  -
    firstname: "Vycheslav"
    lastname: "Karolis"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Logan"
    lastname: "Williams"
    affiliation: "School of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK"
  -
    firstname: "Vanessa"
    lastname: "Kyriakopoulou"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Jelena"
    lastname: "Bozek"
    affiliation: "University of Zagreb, Zagreb, Croatia"
  -
    firstname: "Alena"
    lastname: "Uus"
    affiliation: "School of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK"
  -
    firstname: "Antonios"
    lastname: "Makropoulos"
    affiliation: "ThinkSono, London, United Kingdom"
  -
    firstname: "Andreas"
    lastname: "Schuh"
    affiliation: "Department of Computing, Imperial College London, London, UK"
  -
    firstname: "Lucilio"
    lastname: "Cordero Grande"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Emer"
    lastname: "Hughes"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Anthony"
    lastname: "Price"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Maria"
    lastname: "Deprez"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Mary"
    lastname: "Rutherford"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "A. David"
    lastname: "Edwards"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Daniel"
    lastname: "Rueckert"
    affiliation: "Klinikum rechts der Isar, Technical University of Munich, Munich, Germany"
  -
    firstname: "Stephen"
    lastname: "Smith"
    affiliation: "FMRIB, University of Oxford, Oxford, UK"
  -
    firstname: "Joseph"
    lastname: "Hajnal"
    affiliation: "School of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK"
  -
    firstname: "Tomoki"
    lastname: "Arichi"
    affiliation: "Centre for the Developing Brain, King’s College London, London, UK"
  -
    firstname: "Emma"
    lastname: "Robinson"
    affiliation: "School of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK"

# A title to describe the published resource.
title: "Developing Human Connectome Project spatio-temporal surface atlas of the fetal brain"

# Additional information about the resource, e.g., a brief abstract.
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).

# Lit of keywords the resource should be associated with.
# Give as many keywords as possible, to make the resource findable.
keywords:
  - Surface atlas
  - Fetal MRI
  - Template
  - Brain development

# License information for this resource. Please provide the license name and/or a link to the license.
# Please add also a corresponding LICENSE file to the repository.
license:
  name: "Creative Commons CC0 1.0 Public Domain Dedication"
  url: "https://creativecommons.org/publicdomain/zero/1.0/"



## Optional Fields

# Funding information for this resource.
# Separate funder name and grant number by comma.
funding:
  - "European Union's Seventh Framework Programme (FP/2007-2013), 319456"

# Related publications. reftype might be: IsSupplementTo, IsDescribedBy, IsReferencedBy.
# Please provide digital identifier (e.g., DOI) if possible.
# Add a prefix to the ID, separated by a colon, to indicate the source.
# Supported sources are: DOI, arXiv, PMID
# In the citation field, please provide the full reference, including title, authors, journal etc.
references:
  -
    id: "doi:10.1016/j.neuroimage.2018.06.018"
    reftype: "IsSupplementTo"
    citation: "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"

# Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
resourcetype: Dataset

# Do not edit or remove the following line
templateversion: 1.2