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Related Experiment Videos

Computer generation of random deviates.

J Cormack1, B Shuter

  • 1Radiology Department, Flinders Medical Centre, South Australia.

Australasian Physical & Engineering Sciences in Medicine
|June 1, 1991
PubMed
Summary
This summary is machine-generated.

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This paper reviews computer algorithms for generating random deviates essential for medical physics simulations. It highlights reliable methods for uniform and other distributions, crucial for Monte Carlo simulations in radiology and nuclear medicine.

Area of Science:

  • Medical Physics
  • Computational Science
  • Scientific Simulation

Background:

  • Random deviates are crucial for scientific applications like Monte Carlo simulations in medical physics.
  • Accurate random number generation is vital for modeling physical processes, evaluating formulas, and decision-making models.
  • Applications in medical physics include radiology, radiation therapy, and nuclear medicine, particularly for image noise simulation.

Purpose of the Study:

  • To review computer algorithms for generating uniform random deviates.
  • To discuss algorithms for other probability distributions relevant to medical physicists.
  • To identify potential problems and pitfalls in random number generation.

Main Methods:

  • Review of established computer algorithms for random deviate generation.

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  • Discussion of algorithms producing uniform and non-uniform distributions.
  • Analysis of caveats and common issues in implementation.

    • Main Results:

    • Identification of reliable algorithms for generating high-quality random deviates.
    • Explanation of methods to generate various statistical distributions.
    • Awareness of potential pitfalls in random number generation for simulations.

    Conclusions:

    • High-quality random deviate generators are fundamental for accurate scientific simulations.
    • Understanding algorithm caveats is essential for reliable results in medical physics.
    • Source code for discussed generators is available, facilitating implementation.