ArticleNeuroImage2024
Anatomically constrained tractography of the fetal brain.
Article in NeuroImage, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Charting the Normal Development of Structural Brain Connectivity in Utero Using Diffusion MRI.Human brain mapping · 2026Article
- Transcriptomic divergence of network hubs in the prenatal human brain.Communications biology · 2025Article
- A review on learning-based algorithms for tractography and human brain white matter tracts recognition.Neuroradiology · 2025Review
- FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI.NeuroImage · 2025Article
- A detailed spatiotemporal atlas of the white matter tracts for the fetal brain.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- White Matter Tract Crossing and Bottleneck Regions in the Fetal Brain.Human brain mapping · 2025Article
- Advances in Fetal Brain Imaging.Magnetic resonance imaging clinics of North America · 2024Review
- White matter tract crossing and bottleneck regions in the fetal brain.bioRxiv : the preprint server for biology · 2024Article
- A detailed spatio-temporal atlas of the white matter tracts for the fetal brain.bioRxiv : the preprint server for biology · 2024Article
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.
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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.