ArticleProceedings of SPIE--the International Society for Optical Engineering2018
TRAFIC: Fiber Tract Classification Using Deep Learning.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of automated methods to perform white matter tract segmentation.Frontiers in neuroscience · 2024Pooled it
- Erratum: "Tract-specific white matter microstructure associated with early cognitive development in infants" [Neuroimage Rep 6 (2026) 100336].Neuroimage. Reports · 2026Article
- Tractography-Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure-Informed Supervised Contrastive Learning.Human brain mapping · 2024Article
- Association between prenatal maternal sleep quality, neonatal uncinate fasciculus white matter, and infant negative emotionality.EBioMedicine · 2024Article
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation.NeuroImage · 2023Article
- Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions.Medical image analysis · 2023Article
- Auto-encoded Latent Representations of White Matter Streamlines for Quantitative Distance Analysis.Neuroinformatics · 2022Article
- Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.NeuroImage · 2022Review
- Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations.Frontiers in neuroscience · 2022Article
- Exposure to prenatal maternal distress and infant white matter neurodevelopment.Development and psychopathology · 2021Article
- Novel Deep Learning Network Analysis of Electrical Stimulation Mapping-Driven Diffusion MRI Tractography to Improve Preoperative Evaluation of Pediatric Epilepsy.IEEE transactions on bio-medical engineering · 2020Article
- Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation.Medical image analysis · 2020Article
- Deep white matter analysis: fast, consistent tractography segmentation across populations and dMRI acquisitions.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019Article
- Prediction of postoperative deficits using an improved diffusion-weighted imaging maximum a posteriori probability analysis in pediatric epilepsy surgery.Journal of neurosurgery. Pediatrics · 2019Article
- Objective Detection of Eloquent Axonal Pathways to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery using Diffusion Tractography and Convolutional Neural Networks.IEEE transactions on medical imaging · 2019Article
- Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology.Technology in cancer research & treatmentArticle
- RapidParc: A global-context transformer for parallel, accurate, and lesion-robust tractogram parcellation.Imaging neuroscience (Cambridge, Mass.)Article
- CONTINUITY: CONnectivity Tool with INtegration of sUbcortical regions, regIstration and visualization of TractographY.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We present TRAFIC, a fully automated tool for the labeling and classification of brain fiber tracts. TRAFIC classifies new fibers using a neural network trained using shape features computed from previously traced and manually corrected fiber tracts. It is independent from a DTI Atlas as it is applied to already traced fibers. This work is motivated by medical applications where the process of extracting fibers from a DTI atlas, or classifying fibers manually is time consuming and requires knowledge about brain anatomy. With this new approach we were able to classify traced fiber tracts obtaining encouraging results. In this report we will present in detail the methods used and the results achieved with our approach.
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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.