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

Designing, benchmarking, and applying a Monte Carlo electron transport code

A A al-Beteri1, D E Raeside

  • 1Department of Radiological Sciences, University of Oklahoma Health Sciences Center Oklahoma City.

Computer Methods and Programs in Biomedicine
|April 1, 1993
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

Orthovoltage radiation therapy treatment planning using Monte Carlo simulation: treatment of neuroendocrine carcinoma of the maxillary sinus.

Physics in medicine and biology·1998
Same author

Optimal electron-beam treatment planning for retinoblastoma using a new three-dimensional Monte Carlo-based treatment planning system.

Medical physics·1992
Same author

The accuracy of single-seed dose superposition for I-125 implants.

Medical physics·1989
Same author

An improved electron multiple-scattering distribution for Monte Carlo transport simulation.

Medical physics·1988
Same author

Two-dimensional dose distribution around a commercial 125I seed.

Medical physics·1988
Same author

Monte Carlo simulation of the dose distribution around 125I seeds.

Medical physics·1987
Same journal

A novel Milstein-stochastic epidemiologically-informed neural network for approaching epidemic dynamics: Application to Mpox disease.

Computer methods and programs in biomedicine·2026
Same journal

Accounting for approximation errors using surrogate-based parameter estimation of cardiac mechanics digital twins.

Computer methods and programs in biomedicine·2026
Same journal

Facial iPPG heatmap patterns based on period-aware autoencoder show association with carotid atherosclerosis towards non-contact hemodynamic assessment.

Computer methods and programs in biomedicine·2026
Same journal

Explainable machine learning models predict liver fibrosis risk and outcome in the general population: Development and multi-cohort external validation.

Computer methods and programs in biomedicine·2026
Same journal

Evaluation of surrogate endpoints for survival outcomes using the surrogate package in R.

Computer methods and programs in biomedicine·2026
Same journal

Relative spectral and frication-based descriptors as numerical indicators of place of articulation shifts in fricatives produced by Polish children.

Computer methods and programs in biomedicine·2026
See all related articles

This study introduces a Monte Carlo electron transport code, detailing its simulation of multiple-scattering, ionization, and bremsstrahlung. The code

Area of Science:

  • Medical Physics
  • Computational Physics
  • Radiation Oncology

Background:

  • Accurate simulation of electron transport is crucial for radiation therapy.
  • Existing models may not fully capture complex interactions like multiple scattering and bremsstrahlung.

Purpose of the Study:

  • To present the design and validation of a novel Monte Carlo electron transport code.
  • To assess the code's capability in modeling key physical processes relevant to radiation therapy.

Main Methods:

  • Development of a Monte Carlo code incorporating detailed models for electron scattering, ionization, and bremsstrahlung.
  • Comparison of code predictions against experimental data for validation.

Main Results:

Related Experiment Videos

  • The Monte Carlo code accurately models electron transport phenomena, including multiple scattering, ionization, and bremsstrahlung production.
  • Code predictions show good agreement with experimental measurements.

    • Conclusions:

    • The developed Monte Carlo code provides a reliable tool for simulating electron transport in various media.
    • The code has potential applications in optimizing radiation therapy treatment planning.