Research theme
From scan to outcome: brain growth and neurodevelopment
From routine scans to insight about each pregnancy: how the brain grows, and what that means for development after birth.
Research / From scan to outcome
The problem
A single measurement means little on its own. To spot a brain that is developing differently, we need to know how healthy brains grow across gestation, and to understand how prenatal brain development relates to neurodevelopment after birth.
Our approach
- MeasureExtract brain structure volumes and maturation features from each scan.
- Model growthNormative growth trajectories by gestational age, from large international cohorts.
- Link to outcomesRelate prenatal brain features to neurodevelopment at 2 years.
- EvaluateWork with clinical partners to assess the measures on clinical data.
Key papers
All papers in this theme (21) →- Impaired fetal brain growth and neurodevelopmental deficits at 2 years: deep phenotyping of maternal–fetal pathophysiology
- Clinical Grading of Artificial Intelligence‐Based 3D Fetal Brain Segmentations: A Cross‐Vendor Evaluation of Deep Learning in Fetal Neuroimaging
- Normative growth trajectories of fetal brain regions validated by satisfactory maturation of neurodevelopmental domains at 2 years of age
- Deep learning assessment of fetal brain maturation on 3D ultrasound volumes in early‐onset fetal growth restriction
- Semi-supervised 3D Medical Segmentation from 2D Natural Images Pretrained Model
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Cross‐Modality Comparison of Fetal Brain Phenotypes: Insights From Short‐Interval Second‐Trimester
MRI and Ultrasound Imaging - Exploring Test Time Adaptation for Subcortical Segmentation of the Fetal Brain in 3D Ultrasound
- Anatomically plausible segmentations: Explicitly preserving topology through prior deformations
- Is Your Style Transfer Doing Anything Useful? An Investigation Into Hippocampus Segmentation and the Role of Preprocessing
- Normative spatiotemporal fetal brain maturation with satisfactory development at 2 years
- Brain Ages Derived from Different MRI Modalities are Associated with Distinct Biological Phenotypes
- Prototype Learning for Explainable Brain Age Prediction
- BEAN: Brain Extraction and Alignment Network for 3D Fetal Neurosonography
- Subcortical segmentation of the fetal brain in 3D ultrasound using deep learning
- Learning patterns of the ageing brain in MRI using deep convolutional networks
- Assessment of Regional Cortical Development Through Fissure Based Gestational Age Estimation in 3D Fetal Ultrasound
- Improving U-Net Segmentation with Active Contour Based Label Correction
- Multi-task CNN for Structural Semantic Segmentation in 3D Fetal Brain Ultrasound
- Cortical Plate Segmentation Using CNNs in 3D Fetal Ultrasound
- Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning
- Learning-based prediction of gestational age from ultrasound images of the fetal brain