Joint Prediction of Longitudinal Development of Cortical Surfaces and White Matter Fibers from Neonatal MRI
- Submitting institution
-
University of Dundee
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 28402661
- Type
- D - Journal article
- DOI
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10.1016/j.neuroimage.2017.03.012
- Title of journal
- NeuroImage
- Article number
- -
- First page
- 411
- Volume
- 152
- Issue
- -
- ISSN
- 1053-8119
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper reports the first attempt to build a brain multi-shape model for predicting the evolution trajectory of both cortical surfaces derived from structural MRI and white matter fibres derived from diffusion MRI, using a single baseline timepoint. This work has helped propel subsequent research on predictive modelling of brain development using multiple representations over time. It led to Rekik’s TUBITAK 2232 International Fellowship for Outstanding Researchers and informed the initiative of the NIH-funded Baby Connectome Project based at the University of North Carolina at Chapel Hill and the University of Minnesota.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -