Gamma photon 3D imaging noise suppression method and application

Abstract

The invention relates to a gamma photon 3D imaging noise suppression method and application, belongs to the technical field of industrial detection, and provides an improved OSEM algorithm of ToF datarecombination based on the mapping principle of gamma photon ToF information and positron annihilation positions, a constraint image reconstruction model of a ToF index solution is established, datarecombination is performed on LoR by taking ToF information as an index. System matrix elements are adjusted according to ToF information weight coefficients, a system matrix is compressed by sparsifying the system matrix elements, and image reconstruction efficiencyis improved. an improved OSEM algorithm of solution constraint is adopted for image reconstruction, the contribution of image pixelsto LoR is limited to be matched with the distribution probability of positron annihilation position -ToF curves of the image pixels in ToF information, the purpose of suppressing statistical noise propagation is achieved, and therefore the detection resolution is improved.

Description

technical field [0001] The invention relates to the technical field of industrial detection, in particular to a method and application of gamma photon 3D imaging noise suppression. Background technique [0002] In the aviation propulsion system, complex parts of industrial equipment such as engine parts and tail nozzle aerodynamic flow channels have high material density and complex inner cavity structure. The non-destructive testing of the inner cavity structure and inner wall defects has become an urgent problem in the testing field. Conventional detection methods are limited by factors such as the material density of complex parts and the complexity of the inner cavity structure, and cannot achieve undisturbed and non-destructive high-resolution detection. The gamma photon 3D imaging technology has become a new method for the inspection of complex parts of industrial equipment. In addition, the gamma photon has the advantages of strong penetrating ability and strong anti-...

AI Technical Summary

Problems solved by technology

[0004] The γ-photon image reconstruction OSEM algorithm belongs to the unconstrained optimization algorithm. In the image reconstruction process, it is assumed that the image pixels passed by the LoR contribute to the generation of the LoR according to the corresponding components of the system matrix, and different pixels belonging to the same LoR affect each other. This will lead to statistical noise between different pixels belonging to the same LoR, which will be amplified and propagated, resulting in excessively smooth edges in the reconstructed image, thereby reducing the signal-to-noise ratio of the reconstructed image, and then adversely affecting the detection resolution.

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