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 Experiment Videos

NMR diffusion simulation based on conditional random walk.

H Gudbjartsson1, S Patz

  • 1Dept. of Electr. Eng. & Comput. Sci., MIT, Cambridge, MA.

IEEE Transactions on Medical Imaging
|January 1, 1995
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Treatment outcomes among HIV-positive orphaned and non-orphaned children on antiretroviral therapy in Johannesburg, South Africa.

South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde·2019
Same author

Relationship between Cough-Associated Changes in CSF Flow and Disease Severity in Chiari I Malformation: An Exploratory Study Using Real-Time MRI.

AJNR. American journal of neuroradiology·2018
Same author

Cough-Associated Changes in CSF Flow in Chiari I Malformation Evaluated by Real-Time MRI.

AJNR. American journal of neuroradiology·2015
Same author

Factors such as regulatory proteins, mRNA and miRNA are transported by stem cell specific microparticles that are released into the cerebprospinal fluid following traumatic brain injury (TBI).

Journal of stem cells & regenerative medicine·2014
Same author

Physiology-based MR imaging assessment of CSF flow at the foramen magnum with a valsalva maneuver.

AJNR. American journal of neuroradiology·2013
Same author

Cough-associated headache in patients with Chiari I malformation: CSF Flow analysis by means of cine phase-contrast MR imaging.

AJNR. American journal of neuroradiology·2011
Same journal

LLM-enhanced Neuron Segmentation and Reconstruction in Complex Mouse Brain Images.

IEEE transactions on medical imaging·2026
Same journal

Matrixed-Spectrum Decomposition Accelerated Linear Boltzmann Transport Equation Solver for Fast Scatter Correction in Multi-Spectral CT.

IEEE transactions on medical imaging·2026
Same journal

The Ritz Adjoint Method for MRI Pulse Design.

IEEE transactions on medical imaging·2026
Same journal

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

IEEE transactions on medical imaging·2026
Same journal

Informed-Exploration Reinforcement Learning for Automated Virtual Coronary Intervention Planning.

IEEE transactions on medical imaging·2026
Same journal

4D Reconstruction of Fetal Left Ventricle from Echocardiography via 2.5D Radial Segmentation and Graph-Fourier Reconstruction.

IEEE transactions on medical imaging·2026
See all related articles

This study presents a novel, rapid simulation method for magnetic resonance imaging (MRI) diffusion. The new approach enhances computational efficiency by making results independent of simulation time steps.

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Computational Physics

Background:

  • Conventional nuclear magnetic resonance (NMR) diffusion simulation methods, including Monte Carlo (MC) and finite difference (FD), are often limited by their dependence on simulation time steps.
  • Existing methods like the deterministic convolution method require adequate time steps for accurate spin diffusion simulation.

Purpose of the Study:

  • To introduce a new, highly efficient simulation method for free diffusion under a linear magnetic field gradient.
  • To develop a simulation technique that overcomes the time step dependency of earlier NMR-diffusion models.

Main Methods:

  • Extension of the conventional Monte Carlo (MC) method and the convolution method.
  • Development of a simulation algorithm where results are independent of the simulation time step.

Related Experiment Videos

  • Utilizing the largest possible time step to significantly reduce computation time.

    • Main Results:

    • The proposed method achieves results independent of the simulation time step, unlike previous NMR-diffusion simulation techniques.
    • Demonstrated reduction in computation time by optimizing time step selection.
    • The algorithm shows potential for reducing computation time in restricted diffusion simulations within simple geometries.

    Conclusions:

    • The new simulation method offers a significant speed-up for diffusion MRI by eliminating time step dependency.
    • This approach provides a more computationally efficient alternative for simulating diffusion processes, particularly in linear magnetic field gradients.
    • The algorithm is applicable to reducing computation time for restricted diffusion simulations in specific configurations.