ArticleNeuroinformatics2022
Automated Brain Masking of Fetal Functional MRI with Open Data.
Article in Neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
What it found
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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.
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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
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Roles and applications of artificial intelligence in fetal and placental MRI: a literature review.BMC pregnancy and childbirth · 2026Pooled it
- Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.Biological psychiatry · 2023Pooled it
- A null findings study: graph theoretical analysis of the fetal functional connectome shows no relationships with future autistic traits.Neuroimage. Reports · 2026Article
- Article
- MRI-based Quantification of Ossification Centers in the Human Fetal Atlas and Axis Vertebrae.Current medical imaging · 2026Article
- Human brain R2* transitions across birth from the womb to early infancy.Communications biology · 2025Article
- Measuring the effects of motion corruption in fetal fMRI.Human brain mapping · 2025Article
- Whole Brain MRI Assessment of Age and Sex-Related R2* Changes in the Human Fetal Brain.Human brain mapping · 2025Article
- The developing Human Connectome Project fetal functional MRI release: Methods and data structures.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Trajectories of human brain functional connectome maturation across the birth transition.PLoS biology · 2024Article
- [Research Progress in Magnetic Resonance Imaging of Fetal Ventriculomegaly].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024Review
- Developmental trajectories of the default mode, frontoparietal, and salience networks from the third trimester through the newborn period.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Fetal-BET: Brain Extraction Tool for Fetal MRI.IEEE open journal of engineering in medicine and biology · 2024Article
- Fetal Frontolimbic Connectivity Prospectively Associates With Aggression in Toddlers.Biological psychiatry global open science · 2023Article
- Automatic Ventriculomegaly Detection in Fetal Brain MRI: A Step-by-Step Deep Learning Model for Novel 2D-3D Linear Measurements.Diagnostics (Basel, Switzerland) · 2023Article
- Artificial intelligence applied to fetal MRI: A scoping review of current research.The British journal of radiology · 2023Article
- Funcmasker-flex: An Automated BIDS-App for Brain Segmentation of Human Fetal Functional MRI data.Neuroinformatics · 2023Article
- Review of deep learning and artificial intelligence models in fetal brain magnetic resonance imaging.World journal of clinical cases · 2023Review
- Fetal behavior during MRI changes with age and relates to network dynamics.Human brain mapping · 2023Article
- RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data.Neuroinformatics · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Fetal resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a critical new approach for characterizing brain development before birth. Despite the rapid and widespread growth of this approach, at present, we lack neuroimaging processing pipelines suited to address the unique challenges inherent in this data type. Here, we solve the most challenging processing step, rapid and accurate isolation of the fetal brain from surrounding tissue across thousands of non-stationary 3D brain volumes. Leveraging our library of 1,241 manually traced fetal fMRI images from 207 fetuses, we trained a Convolutional Neural Network (CNN) that achieved excellent performance across two held-out test sets from separate scanners and populations. Furthermore, we unite the auto-masking model with additional fMRI preprocessing steps from existing software and provide insight into our adaptation of each step. This work represents an initial advancement towards a fully comprehensive, open-source workflow, with openly shared code and data, for fetal functional MRI data preprocessing.
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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.