Method for renormalization of X-ray multiple scattering simulation

Abstract

The invention provides a method for renormalization of X-ray multiple scattering simulation. The method comprises a first step of generating a low-difference sequence with the length of m in [0,1]<3n> space, enabling n to be scattering times and be a positive integer larger than 1, and enabling m to be the sample number; a second step of generating a scattering point sequence matched with the geometrical shape of a die body by performing isomorphic mapping transformation on the low-difference sequence; a third step of forming m photon paths for each detector grid point through the scattering point sequence; a fourth step of performing renormalization processing on each photon path among the m photon paths; a fifth step of determining the probability density of photons reaching the detector grid points through n-time scattering along each photon path after renormalization processing; and a sixth step of obtaining scattering intensity of each detector grid point according to the probability density of the photons through n-time scattering along each photon path after renormalization processing. The method can improve multiple scattering simulation efficiency and eliminate errors caused by die body edge incontinuity.

Description

【Technical field】 [0001] The invention relates to the technical field of medical image processing, in particular to a renormalization method for X-ray multiple scattering simulation. 【technical background】 [0002] Numerical simulation of scattering based on geometric model is the basis of X-ray scattering correction technology. The complex distribution of scattered radiation in diagnostic radiology is commonly studied by performing Monte Carlo simulations on voxelized object models obtained from reconstructed CT images for the purpose of scatter correction for X-rays. [0003] In the existing Monte Carlo X-ray scattering simulation, a series of pseudo-random numbers or quasi-random sequences are generally used to determine the exit fan angle, opening angle and projection depth of the photons, and track the arrival of each beam of photons at the grid point of the detector. probability and integrated to obtain the X-ray scattering distribution. As described in the literatur...

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Problems solved by technology

Although this method makes full use of the low-variance nature of the quasi-random sequence, the variance of the Monte Carlo simulation integration algorithm is minimized, and the amount of calculation is greatly reduced. The distance between random points is so close that the variance of multiple scattering diverges and the integral does not converge

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