ArticlePLoS computational biology2016
Ensemble Tractography.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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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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Who cites it
70 citing papers in PubMed.
- A high-resolution functional network-organized atlas of human superficial white matter from ultra-high-field diffusion MRI.iScience · 2026Article
- Trait-Relevant Tasks Improve Personality Prediction From Structural-Functional Brain Network Coupling.Human brain mapping · 2026Article
- Structural signatures of synergy and redundancy in human brain function.bioRxiv : the preprint server for biology · 2026Article
- Controlling the human connectome with spatially diffuse input signals.Communications biology · 2026Article
- Reconstructing the human brain's wiring diagram from axons up.Trends in neurosciences · 2026Review
- Real-Time Tractography-Assisted Neuronavigation for Transcranial Magnetic Stimulation.Human brain mapping · 2025Article
- Tractography-Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure-Informed Supervised Contrastive Learning.Human brain mapping · 2024Article
- A Virtual In Vivo Dissection and Analysis of Socioaffective Symptoms Related to Cerebellum-Midbrain Reward Circuitry in Humans.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- A prominent vertical occipital white matter fasciculus unique to primate brains.Current biology : CB · 2024Article
- A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity.Nature communications · 2024Article
- Tractometry of Human Visual White Matter Pathways in Health and Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- Associative white matter tracts selectively predict sensorimotor learning.Communications biology · 2024Article
- Associations of behavioral problems with white matter circuits connecting to the frontal lobes in school-aged children born at term and preterm.Neuroimage. Reports · 2024Article
- Influence of Diffusion Time and Temperature on Restricted Diffusion Signal: A Phantom Study.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Article
- Early, low-dose hydrocortisone and near-term brain connectivity in extremely preterm infants.Pediatric research · 2024Article
- Controlling the human connectome with spatially diffuse input signals.bioRxiv : the preprint server for biology · 2024Article
- Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains.Communications biology · 2024Article
- Structural volumetric and Periodic Table DTI patterns in Complex Normal Pressure Hydrocephalus-Toward the principles of a translational taxonomy.Frontiers in human neuroscience · 2024Article
- Article
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Tractography uses diffusion MRI to estimate the trajectory and cortical projection zones of white matter fascicles in the living human brain. There are many different tractography algorithms and each requires the user to set several parameters, such as curvature threshold. Choosing a single algorithm with specific parameters poses two challenges. First, different algorithms and parameter values produce different results. Second, the optimal choice of algorithm and parameter value may differ between different white matter regions or different fascicles, subjects, and acquisition parameters. We propose using ensemble methods to reduce algorithm and parameter dependencies. To do so we separate the processes of fascicle generation and evaluation. Specifically, we analyze the value of creating optimized connectomes by systematically combining candidate streamlines from an ensemble of algorithms (deterministic and probabilistic) and systematically varying parameters (curvature and stopping criterion). The ensemble approach leads to optimized connectomes that provide better cross-validated prediction error of the diffusion MRI data than optimized connectomes generated using a single-algorithm or parameter set. Furthermore, the ensemble approach produces connectomes that contain both short- and long-range fascicles, whereas single-parameter connectomes are biased towards one or the other. In summary, a systematic ensemble tractography approach can produce connectomes that are superior to standard single parameter estimates both for predicting the diffusion measurements and estimating white matter fascicles.
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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.