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The use of importance sampling techniques to improve the efficiency of photon tracking in emission tomography simulations
Author(s) -
Haynor David R.,
Harrison Robert L.,
Lewellen Thomas K.
Publication year - 1991
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.596615
Subject(s) - monte carlo method , sampling (signal processing) , photon , computer science , monte carlo method for photon transport , algorithm , computational physics , medical physics , computational science , optics , physics , hybrid monte carlo , detector , markov chain monte carlo , mathematics , statistics , telecommunications
Monte Carlo simulations are widely used to study the transmission and scattering of γ rays. Use of this method for simulations of emission tomographs suffers from geometric inefficiency resulting from the low solid angle of acceptance of most tomograph designs. We have applied several importance sampling techniques—stratification, forced detection, and weight control through Russian roulette and splitting—to increase the computational efficiency of the Monte Carlo method 10‐ to 300‐fold. A description of these techniques, their validation, and sample performance results are given. Application of importance sampling methods makes it practical to study photon scattering in heterogeneous attenuators on workstations and minicomputers.