CT system geometric correction effect verification method and device

Abstract

The invention relates to a CT system geometric correction effect verification method and device. The method includes the steps that a preset assessment motif is scanned to obtain a projection image of the assessment motif; a three-dimensional image of the assessment motif is reconstructed according to geometric correction parameters and the projection image of the assessment motif; an image to be processed is segmented from the three-dimensional image, and the edge of a circle in the image to be processed is detected; the number of points in the circle, the sum of CT values of the points in the circle, the number of points outside the circle and the sum of CT values of the points outside the circle in the image to be processed are counted; the CT average value of the points in the circle, the CT average value of the points outside the circle and absolute values of the CT average value of the points in the circle and the CT average value of the points outside the circle are calculated to serve as assessment indexes; assessment indexes corresponding to the geometric correction parameters are compared to conclude whether the geometric correction effects of the geometric correction parameters are good. The method and device can improve accuracy of the geometric correction effect of CT images.

Description

technical field [0001] The invention relates to the field of computer tomography (Computed Tomography, CT), in particular to a method and a device for inspecting the geometric correction effect of a CT system. Background technique [0002] CT scans a layer of a certain thickness of a certain part of the human body with an X-ray beam. The X-rays that pass through this layer are received by the detector and converted into visible light, which is converted from photoelectricity into an electrical signal, and then converted by an analog / digital converter. It is a number, which is input into the computer for processing. The processing of CT image formation is like dividing the selected slice into several cuboids with the same volume, which are called voxels. The scanned information is calculated to obtain the X-ray attenuation coefficient (or absorption coefficient) of each voxel, and then arranged into a digital matrix. Through the digital / analog converter, each number in the ...

AI Technical Summary

Problems solved by technology

[0005] However, because the geometric correction parameters cannot directly reflect the geometric correction effect, the existing evaluation methods for the geometric correction effect are based on the observation of CT images by experienced personnel.

This calibration method is often affected by factors such as personal experience and the fineness of human eye observation, and it is difficult to accurately test the geometric correction effect

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