ArticleHuman brain mapping2019
Fetal cortical surface atlas parcellation based on growth patterns.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Fetal brain MRI atlases and datasets: A review.NeuroImage · 2024Pooled it
- Age-Specific Contrast Optimization of bSSFP in Fetal Brain.Magnetic resonance in medicine · 2026Article
- Surface expansion regionalization of the hippocampus in early brain development.Developmental cognitive neuroscience · 2026Article
- MRI-based spatio-temporal atlas of ganglionic eminence.European radiology experimental · 2026Article
- Cortical folding and thickness characteristics of gray matter in fetuses with non-severe ventriculomegaly.BMC pediatrics · 2026Article
- A subject-specific reversible folding model reveals geometry-driven white-matter organization.bioRxiv : the preprint server for biology · 2025Article
- Molecular signatures of cortical expansion in the human foetal brain.Nature communications · 2024Article
- Molecular signatures of cortical expansion in the human fetal brain.bioRxiv : the preprint server for biology · 2024Article
- Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net.Frontiers in neuroscience · 2024Article
- Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Longitudinal mapping of the development of cortical thickness and surface area in rhesus macaques during the first three years.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Maturational networks of human fetal brain activity reveal emerging connectivity patterns prior to ex-utero exposure.Communications biology · 2023Article
- Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates.Developmental cognitive neuroscience · 2023Review
- Neuromorphological Atlas of Human Prenatal Brain Development: White Paper.Life (Basel, Switzerland) · 2023Article
- GEOMETRIC CONSTRAINED DEEP LEARNING FOR MOTION CORRECTION OF FETAL BRAIN MR IMAGES.Proceedings. IEEE International Symposium on Biomedical Imaging · 2023Article
- MRI-based structural covariance network in early human brain development.Frontiers in neuroscience · 2023Article
- Spatiotemporal Atlas of the Fetal Brain Depicts Cortical Developmental Gradient.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Anatomy-Guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI.Machine learning in medical imaging. MLMI (Workshop) · 2020Article
- A novel approach to multiple anatomical shape analysis: Application to fetal ventriculomegaly.Medical image analysis · 2020Article
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11 authors.
Funding
Abstract
Defining anatomically and functionally meaningful parcellation maps on cortical surface atlases is of great importance in surface-based neuroimaging analysis. The conventional cortical parcellation maps are typically defined based on anatomical cortical folding landmarks in adult surface atlases. However, they are not suitable for fetal brain studies, due to dramatic differences in brain size, shape, and properties between adults and fetuses. To address this issue, we propose a novel data-driven method for parcellation of fetal cortical surface atlases into distinct regions based on the dynamic "growth patterns" of cortical properties (e.g., surface area) from a population of fetuses. Our motivation is that the growth patterns of cortical properties indicate the underlying rapid changes of microstructures, which determine the molecular and functional principles of the cortex. Thus, growth patterns are well suitable for defining distinct cortical regions in development, structure, and function. To comprehensively capture the similarities of cortical growth patterns among vertices, we construct two complementary similarity matrices. One is directly based on the growth trajectories of vertices, and the other is based on the correlation profiles of vertices' growth trajectories in relation to a set of reference points. Then, we nonlinearly fuse these two similarity matrices into a single one, which can better capture both their common and complementary information than by simply averaging them. Finally, based on this fused similarity matrix, we perform spectral clustering to divide the fetal cortical surface atlases into distinct regions. By applying our method on 25 normal fetuses from 26 to 29 gestational weeks, we construct age-specific fetal cortical surface atlases equipped with biologically meaningful parcellation maps based on cortical growth patterns. Importantly, our generated parcellation maps reveal spatially contiguous, hierarchical and bilaterally relatively symmetric patterns of fetal cortical surface development.
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