Large diameter pipeline wall outside CT local scanning imaging method

Abstract

The invention relates to a large diameter pipeline wall outside CT local scanning imaging method, and belongs to the technical field of CT scanning imaging. The method comprises the following steps: a radiation source and a detector are arranged in a circular track surrounding the center of a pipeline to be detected, and the detector is arranged in an offset manner; the radiation source and the detector circularly move along the circular track to scan in order to obtain the projection data of the annular region outside the pipeline to be detected; and a TVM-POCS reconstruction algorithm and a region scale fitting segmentation technology are combined to reconstruct the image of the annular region outside the pipeline according to the projection data. The large diameter pipeline wall outside CT local scanning imaging method has the advantages of simple and easy scanning mode, short scanning time, low radiation dose, satisfactory solving of the cross cutting problem of the projection data, great reduction of the reconstruction artifact, satisfactory solving of the problem of reconstructed image gray scale unevenness caused by ray beam hardening, and good quality of the finally displayed local reconstruction image of the annular region outside the pipeline.

Description

technical field [0001] The invention belongs to the technical field of CT scanning imaging, and relates to a CT local scanning imaging method for the outside of a large-diameter pipeline wall. Background technique [0002] In actual industrial production, industrial parts such as pipe walls inevitably have cracks and defects in the process of manufacture and use. As they are subjected to alternating loads during use, cracks and defects may suddenly cause component damage during use. Fatigue fracture is extremely harmful. Therefore, timely detection of cracks and defects inside the pipe wall is of great significance to prevent disasters and reduce economic losses. [0003] In the prior art, X-ray CT imaging detection can reconstruct internal defects of objects non-destructively, accurately and quickly. However, in the actual detection process, the following situations often occur: the size of the object to be reconstructed is larger than the size of the detector, so that th...

AI Technical Summary

Problems solved by technology

Due to the incompleteness of projection data, the reconstruction results of traditional analytical reconstruction algorithms such as FBP (Filtered back-projection) algorithm have serious strip artifacts, which cannot meet the requirements of practical applications.

Frank Natterer developed a regularization method and pointed out that under ideal conditions, the two-dimensional inverse Radon transform of the external reconstruction problem has a unique solution, but the solution is extremely unstable when noise is involved

E.T.Quinto made an in-depth study on the SVD (Singular Value Decomposition, singular value decomposition) method of the external CT reconstruction problem, but because the singular value of the projection coefficient matrix may be small, the solution is ill-posed

Therefore, the above method is difficult to be used for image reconstruction of real noisy projection data

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