ArticleScientific data2021
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Fetal brain MRI atlases and datasets: A review.NeuroImage · 2024Pooled it
- Deep learning based gestational age estimation from multi-view fetal brain magnetic resonance imaging.Pediatric radiology · 2026Article
- A multicentre benchmark dataset for comprehensive landmark-based fetal ultrasound biometry.Scientific reports · 2026Article
- Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026Review
- Advances in automated fetal brain MRI segmentation and biometry: Insights from the FeTA 2024 challenge.Medical image analysis · 2026Article
- Detailed Delineation of the Fetal Brain in Diffusion MRI via Multi-Task Learning.IEEE transactions on medical imaging · 2026Article
- AI-Driven Clinical Decision Support System for Automated Ventriculomegaly Classification from Fetal Brain MRI.Journal of imaging · 2025Article
- Large-vocabulary segmentation for medical images with text prompts.NPJ digital medicine · 2025Article
- Baby Open Brains: An open-source dataset of infant brain segmentations.Scientific data · 2025Article
- Revisiting model scaling with a U-net benchmark for 3D medical image segmentation.Scientific reports · 2025Article
- TMagnetic resonance in medicine · 2025Article
- A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain.Scientific data · 2025Article
- Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results.IEEE transactions on medical imaging · 2025Article
- Article
- Altered Connectome Topology in Newborns at Risk for Cognitive Developmental Delay: A Cross-Etiologic Study.Human brain mapping · 2025Article
- Longitudinal Assessment of Abnormal Cortical Folding in Fetuses and Neonates With Isolated Non-Severe Ventriculomegaly.Brain and behavior · 2025Article
- Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool.Scientific reports · 2024Article
- Baby Open Brains: An Open-Source Repository of Infant Brain Segmentations.bioRxiv : the preprint server for biology · 2024Article
- Article
- A Unified Pipeline for Simultaneous Brain Tumor Classification and Segmentation Using Fine-Tuned CNN and Residual UNet Architecture.Life (Basel, Switzerland) · 2024Article
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Authors and funding
20 authors.
Funding
Abstract
It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders. To facilitate this analysis, automatic multi-tissue fetal brain segmentation algorithms are needed, which in turn requires open datasets of segmented fetal brains. Here we introduce a publicly available dataset of 50 manually segmented pathological and non-pathological fetal magnetic resonance brain volume reconstructions across a range of gestational ages (20 to 33 weeks) into 7 different tissue categories (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, deep grey matter, brainstem/spinal cord). In addition, we quantitatively evaluate the accuracy of several automatic multi-tissue segmentation algorithms of the developing human fetal brain. Four research groups participated, submitting a total of 10 algorithms, demonstrating the benefits the dataset for the development of automatic algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.