ArticleScientific data2025
Baby Open Brains: An open-source dataset of infant brain segmentations.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Application of artificial intelligence in paediatric oncology imaging.Pediatric radiology · 2026Review
- AI segmentation requires accounting for brain size to maintain performance on developmental MRI cohorts.bioRxiv : the preprint server for biology · 2026Article
- BIBSNet: A deep learning baby image brain segmentation network for MRI scans.Developmental cognitive neuroscience · 2026Article
- Trajectories of hippocampal subregion development in the first years of life and their association with school-aged episodic memory outcomes.bioRxiv : the preprint server for biology · 2026Article
- The Development of Lateralized Brain Oscillations in Infants: Lessons From Autism.Developmental psychobiology · 2025Article
- Deep infant brain segmentation from multi-contrast MRI.Conference record. Asilomar Conference on Signals, Systems & Computers · 2025Article
Corrections and comments
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Authors and funding
39 authors.
Funding
Abstract
Reproducibility of neuroimaging research on infant brain development remains limited due to highly variable processing approaches. Progress towards reproducible pipelines is limited by a lack of benchmarks such as gold-standard brain segmentations. These segmentations are limited by the difficulty of infant brain segmentations, which require extensive neuroanatomical knowledge and are time-consuming in nature. Addressing this, we constructed the Baby Open Brains (BOBs) Dataset, an open source resource of manually curated and expert reviewed infant brain segmentations. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1-9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.
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What OpenQuestion holds
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.