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Streamline tractography of the fetal brain in utero with machine learning

Imaging Neuroscience(2025)10.1162/imag_a_00537Source: DataRank Database

Streamline tractography of the fetal brain in utero with machine learning is a research paper published in Imaging Neuroscience (2025). On theSindex it has a DataRank of 0. It has been cited 2 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (16 grants)Impact (FWCI 0.69)OA: goldTopics (32)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Camilo Calixto ORCID,Simon K. Warfield ORCID,Davood Karimi ORCID,Weide Liu ORCID

Live enrichment

PubMed:40800807 PMC:PMC12319953 OpenAlex:https://openalex.org/W4402428781

National Institute of Neurological Disorders and Stroke

Grant: R01NS128281

Eunice Kennedy Shriver National Institute of Child Health and Human Development

Grant: R01HD110772

National Institutes of Health

Grant: R01 EB018988

National Institutes of Health

Grant: R01 LM013608

National Institutes of Health

Grant: R01 EB019483

National Institutes of Health

Grant: R01 NS106030

National Institutes of Health

Grant: R01 NS124212

Director of the NIH

Grant: S10 OD025111

National Institutes of Health

Grant: 5R01HD110772-02

Accurate, reliable, and interpretable machine learning for assessment of neonatal and pediatric brain micro-structure

National Institutes of Health

Grant: 5R01EB018988-04

Motion-robust super-resolution diffusion weighted MRI of early brain development

National Institutes of Health

Grant: 5R01LM013608-04

Machine learning algorithms to analyze large medical image datasets

National Institutes of Health

Grant: 1S10OD025111-01

Acquisition of a Siemens 3T MRI for Research Imaging

National Institutes of Health

Grant: 5R01NS106030-04

Advancing microstructural and vascular neuroimaging in perinatal stroke

National Institutes of Health

Grant: 1R01EB019483-01A1

Improved Motion Robust MRI of Children

National Institutes of Health

Grant: 5R01NS128281-03

Enabling the Assessment of Fetal Brain Development and Degeneration with Machine Learning

National Institutes of Health

Grant: 5R01NS124212-03

Motion Compensated fMRI for Pre-Surgical Planning in Epilepsy

FWCI

0.69

Citation Percentile

0.6%

Citation Trend

2024

2025

goldLicense: cc-by

journalhttps://doi.org/10.1162/imag_a_00537

publisherhttps://doi.org/10.1162/imag_a_00537

publisherhttps://direct.mit.edu/imag/article-pdf/doi/10.1162/imag_a_00537/2509674/imag_a_00537.pdf

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39253631

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40800807

Fields of Study

Advanced Neuroimaging Techniques and ApplicationsFetal and Pediatric Neurological DisordersNeonatal and fetal brain pathology0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

TractographyDiffusion MRIArtificial intelligenceWhite matterComputer sciencePattern recognition (psychology)Context (archaeology)SegmentationComputer visionMagnetic resonance imagingGeologyRadiologyMedicineMachine LearningFetal BrainDeveloping BrainFOS: Computer and information sciencesComputer Science - Machine LearningArtificial Intelligence (cs.AI)Computer Science - Artificial IntelligenceQuantitative Biology - Neurons and CognitionComputer Vision and Pattern Recognition (cs.CV)FOS: Biological sciencesComputer Science - Computer Vision and Pattern RecognitionNeurons and Cognition (q-bio.NC)Research ArticleMachine Learning (cs.LG)