Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Orthogonal Trajectories01:26

Orthogonal Trajectories

282
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
282

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

GEORCE: a fast new control algorithm for computing geodesics.

Information geometry·2026
Same author

Risks of automation in medicine - a review article for the obstetrics case.

Danish medical journal·2026
Same author

Biomonitoring with bees and bee products: multielement profiles including technology-critical elements.

Monatshefte fur chemie·2026
Same author

Visualizing stability: a sensitivity analysis framework for t-SNE embeddings.

Frontiers in bioinformatics·2026
Same author

The combined use of cervical ultrasound and deep learning improves the detection of patients at risk for spontaneous preterm delivery.

American journal of obstetrics and gynecology·2025
Same author

A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation.

NPJ climate and atmospheric science·2025
Same journal

LiftReg: Limited Angle 2D/3D Deformable Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Inverse Consistency by Construction for Multistep Deep Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Equivariant Filters for Efficient Tracking in 3D Imaging.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Lobar Lung Density Embeddings with a Transformer encoder (LobTe) to predict emphysema progression in COPD.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

uniGradICON: A Foundation Model for Medical Image Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
See all related articles

Related Experiment Video

Updated: Apr 22, 2026

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
13:26

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

11.3K

Probabilistic shortest path tractography in DTI using Gaussian Process ODE solvers.

Michael Schober, Niklas Kasenburg, Aasa Feragen

    Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
    |October 17, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel Gaussian Process tractography algorithm for brain connectivity estimation using diffusion tensor imaging. The method quantifies and visualizes uncertainty, improving precision and expert agreement in mapping neural pathways.

    More Related Videos

    DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
    10:05

    DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

    Published on: August 26, 2014

    13.0K
    Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
    17:06

    Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

    Published on: November 8, 2012

    25.9K

    Related Experiment Videos

    Last Updated: Apr 22, 2026

    Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
    13:26

    Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

    Published on: August 11, 2016

    11.3K
    DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
    10:05

    DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

    Published on: August 26, 2014

    13.0K
    Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
    17:06

    Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

    Published on: November 8, 2012

    25.9K

    Area of Science:

    • Neuroimaging
    • Computational Neuroscience
    • Medical Image Analysis

    Background:

    • Diffusion tensor imaging (DTI) tractography estimates brain connectivity by analyzing local water diffusion.
    • Current DTI tractography methods suffer from low resolution and noise, limiting the precision of identified neural connections.
    • Accurate brain connectivity mapping is crucial for understanding neurological disorders and guiding surgical interventions.

    Purpose of the Study:

    • To develop an advanced tractography algorithm for more precise brain connectivity estimation.
    • To incorporate probabilistic numerics and Gaussian Processes for quantifying and visualizing uncertainty in tractography.
    • To evaluate the performance of the proposed algorithm against existing metrics and expert assessments.

    Main Methods:

    • Utilized probabilistic numerics to estimate connectivity between regions of interest.
    • Developed a Gaussian Process tractography algorithm to model and represent posterior uncertainty.
    • Applied uncertainty quantification for visualizing individual tracts and generating heat maps of tract locations.
    • Performed quantitative evaluations comparing different metrics and algorithms, including the adjoint metric.

    Main Results:

    • The Gaussian Process tractography algorithm successfully quantified and visualized the uncertainty associated with estimated brain connections.
    • Visualization of uncertainty aided in understanding the reliability of individual tract reconstructions and overall connectivity patterns.
    • Quantitative analysis demonstrated that the adjoint metric, when combined with the proposed algorithm, yielded results with the highest agreement with expert-defined pathways.
    • The algorithm showed improved precision in identifying neural connections compared to conventional methods.

    Conclusions:

    • The proposed Gaussian Process tractography algorithm offers a robust approach for estimating brain connectivity with quantifiable uncertainty.
    • Incorporating uncertainty visualization enhances the interpretation and reliability of tractography results.
    • The combination of the adjoint metric and the Gaussian Process algorithm represents a significant advancement in accurate and precise brain connectivity mapping.