Method of acquiring chromatographic gamma scanning image of nuclear wastebin

Abstract

The invention discloses a method of acquiring a chromatographic gamma scanning image of a nuclear wastebin. The method comprises the steps that chromatographic gamma scanning is performed on the nuclear wastebin, and transmission measurement projection data is acquired; a projection equation is established according to the transmission measurement projection data; a non-minimum optimization algorithm is utilized to solve the projection equation, and a non-minimum optimal solution is obtained; and the non-minimum optimal solution is used as an iteration initial value of an MLEM algorithm, and the MLEM algorithm is utilized to reconstruct the image. According to the method, the non-iteration non-minimum optimization algorithm is utilized to calculate and solve the projection equation, the solved non-minimum optimal solution is used as the iteration initial value of the MLEM algorithm, therefore, the randomness and contingency of the traditional MLEM algorithm can be avoided, the precision and accuracy of the reconstructed image are improved, the automatic degree of computer image reconstruction is increased, the workload is lowered, the process is simplified, and working efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for obtaining a tomographic gamma scan image of a nuclear waste barrel. Background technique [0002] At present, image reconstruction methods can be mainly classified into two categories: one is analytical reconstruction algorithm based on Radon transform, and the other is iterative reconstruction algorithm based on the idea of ​​solving equations. The iterative algorithm has good reconstruction effect, stable process, and is suitable for complex projection situations. It is the most commonly used method in Tomographic gamma scanning (TGS) image reconstruction. However, compared with the analytical method, the calculation format is more complicated and the amount of calculation Major disadvantages. How to effectively improve the algorithm convergence speed and final reconstruction accuracy of the iterative algorithm in the reconstruction process is a research ...

AI Technical Summary

Problems solved by technology

Accurate estimation of the initial value is a necessary condition to ensure the convergence and accuracy of the iteration, and it is also related to the convergence speed. However, the traditional empirical value method or random number method is blind, and the result error is large or even does not converge.

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