Efficient sampling algorithms for Monte Carlo based treatment planning

J. J. Demarco, T. D. Solberg, I. Chetty, J. B. Smathers

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed.

Original languageEnglish (US)
Pages (from-to)229-234
Number of pages6
JournalRadiation Physics and Chemistry
Issue number3
StatePublished - Sep 1998


  • Monte Carlo
  • Radiotherapy
  • Sampling

ASJC Scopus subject areas

  • Radiation


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