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Computational framework to assess brain maturation in small vulnerable newborns, from womb to cot

CORDIS · observation · Publication date unknown

metrics (e.g., head circumference), with pre- and post-birth measurements rarely integrated. WOMB2COT will tackle these hurdles with a technically ambitious programme that combines US imaging with deep learning (DL) and computational neuroanatomy. We will develop advanced DL-based US image analysis techniques, including neural radiance fields, image registration, and domain adaptation, to quantify brain development in the most vulnerable preterm infants compared to their expected in utero growth trajectory. This approach will utilise longitudinal cUS scans collected in neonatal intensive care units (NICUs), offering a more detailed, objective evaluation of neonatal brain growth and bridging the care gap as these infants transition from intra- to extra-uterine life. We aim to reduce US imaging artefacts (e.g., acoustic shadows) and enhance structural specificity to sub-millimetre resolution to extract brain morphometrics (BMs), surpassing coarse and qualitative assessments. Building on our population atlas of healthy brain maturation (Nature 2023) and advanced computational tools

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recordType

award

status

SIGNED

region

EU

value

1499990

unit

EUR