Industrial computed tomography (CT) image reconstruction centralized positioning method based on point spread function

Abstract

The invention discloses an industrial computed tomography (CT) image reconstruction centralized positioning method based on a point spread function, and relates to the field of CT scan image construction. The industrial CT image reconstruction centralized positioning method particularly includes the following steps: (1) obtaining the tomographic projection data of middle portion of a to-be-measured disc in the thickness direction, obtaining a projection sonogram; (2) calculating the marginal location x 0 of the center of mass; (3) letting that the offset x of the rotation center of the disc is be the range of from x 0 minus delta to x 0 plus delta, reconstructing the CT images corresponding each offset x by applying a filtered back projection reconstruction algorithm; and (4) determining the height h of the point spread function (PSF) of disc margin in each reconstructed CT image, fitting the function relationship of an image reconstruction center offset x and the height h of the PSF of disc margin, and calculating the image reconstruction center offset.

Description

technical field [0001] The invention relates to the field of CT scan image construction, in particular to a method for center positioning of industrial CT image reconstruction. Background technique [0002] Image reconstruction of the third-generation CT scan is based on the assumption that when the fan-shaped beam is projected in rotation, the center ray passes through the center of rotation, or the position of the rotation center in the fan-shaped ray beam is known. The actual CT system must do this One point is very difficult. In the initial debugging stage of the equipment, it takes a tedious trial and error process to meet the accuracy requirements; and when the equipment is used for a period of time, due to factors such as environment and load changes, the position of the rotation center will drift, and it will be laborious and time-consuming to find the correct position. . There are many solutions to this problem, mainly iterative method, sinogram center of gravity m...

AI Technical Summary

Problems solved by technology

[0003] Fu Jian and others solved the position offset of each projection value through the relationship between the offset of the ray source and the offset of any point on the workpiece projected on the detector, and moved the ray source multiple times, and iteratively reconstructed the CT image. Determine the image reconstruction center, the positioning accuracy of this method is not high, and the use of image signal-to-noise ratio to judge the clarity of image reconstruction cannot achieve the expected effect

[0004] According to the principle of symmetry of the projected sinogram about the center of rotation, Zhang Wei et al. first segment the projected sinusoidal image, and then find the projected centroid of the object projected in all directions, and finally weight all centroid positions to find the mean value. The advantages of this method are: Reduce the influence of noise, but when the density of the scanned object is low, the projection image segmentation is inaccurate, resulting in low positioning accuracy

[0005] Li Baolei and others used the symmetric relationship between the projected sinogram and the rotation center under the third-generation CT scan and 360° rotation mode, that is, the relationship between the area integral on the left side of the rotation center and the area integral on the right side of the projected value on the sinogram is equal to calculate the rotation The center position, the calculation accuracy of this method is at the pixel level, and it is greatly affected by noise

[0006] Liu T et al. used the single-point model method to calculate the offset of the rotation center. This method fixed a steel wire on the turntable, and the turntable rotated 360° around the rotation center. The extreme value of the wire projection data was used to solve the image reconstruction center. The disadvantage of the model is that it cannot avoid the error introduced by the volume effect

[0007] Another relative angle method based on the sinogram is to use the characteristic that the projection values ​​with a rotation angle difference of 180° in the sinogram are equal, and take the minimum position corresponding to the mean value of the difference between the two sets of projections with an angle difference of 180° as the reconstruction center. This method cannot Avoid the volume effect introduced by the detector with a certain width, the accuracy is not high, and this method requires the radiation source dose to be very stable

Images