A phantom method for high-precision calibration of cone-beam ct rotation center and sod

Abstract

Based on the traditional calibration method, a phantom method for calibrating the rotation center and SOD of the cone beam CT with high precision is provided, which is simple and efficient to improve the calibration precision of the parameters, the CT geometric parameters are calibrated by using the traditional method initially, after the calibration is completed, the steel needle phantom is used for CT scanning, image reconstruction, and the reconstructed image is post-processed, the rotation center and the distance from the ray source to the rotation center (SOD parameter) are fine-tuned, so that the imaging section of the steel needle obtained is small, the steel needle section characteristics are met, the center area is not distorted, and the distance between the steel needles meets the actual steel needle spacing.

Description

TECHNICAL FIELD

[0001] The application relates to a phantom method for calibrating a cone beam CT, in particular to a phantom method for calibrating a rotation center and a SOD of a cone beam CT with high precision. BACKGROUND

[0002] In the past 20 years, cone beam computed tomography (CBCT) has been widely used in the field of dentistry as a three-dimensional X-ray imaging technology. CBCT adopts a traditional CT technology, which emits X-rays from one side of the patient and the detector receives the attenuated X-rays from the other side, while the X-ray tube and the detector rotate around the patient. The exposure during the rotation scan can adopt continuous signal exposure or pulse signal exposure. Pulse signal can effectively reduce the exposure time of the patient in the X-ray and reduce the X-ray dose received by the patient. CBCT can accurately describe the multi-planar details of the maxillofacial bone structure and the surrounding soft tissue, which breaks through the limitations of traditional two-dimensional dental imaging. Three-dimensional image reconstruction is the core component of CBCT imaging in terms of calculation. In recent years, there are more and more algorithms for cone beam CT image reconstruction, which are mainly divided into two categories: analytical method and iterative method. The analytical method is a reconstruction method that uses Radon transform as the theoretical basis to analyze the projection data in the continuous domain, and then discretizes the calculation. The algorithm widely used in the current analytical method is the FDK approximate reconstruction algorithm proposed by Davis and Kress, which can effectively reduce the operation amount and shorten the reconstruction time, so the algorithm is more commonly used in CBCT. The iterative method uses a certain optimization method, which starts from the initial projection image, compares the theoretical projection point with the actual projection value obtained at present, uses the step-by-step approximation strategy, and constantly reduces the gap between the two, and then finds the global optimal solution. Using the iterative method can obtain high-resolution projection data and strong anti-noise ability, but in practical application, it is difficult to find the optimal solution for multiple frames of data, the calculation amount is huge, the requirement for machine hardware is high, the cost is large, and the current application is not very widespread.

[0003] But no matter which reconstruction algorithm, the need to obtain projection data, accurate projection data for subsequent reconstruction calculation and image clarity played a key role. Therefore, in order to obtain more ideal projection data, need to ensure that the object and machine in the process of rotation to keep stable, the detection of the flat plate and the line of the ray source focus to the flat plate center keep vertical, and require the detector center, the rotation center and the ray source focus three points in a straight line. But in real life, mechanical assembly, moving and small offset of the turntable and other factors will cause the flat plate position offset, resulting in the use of theoretical rotation center parameters in the calculation of the reconstructed image, so that the image appears artifacts. The distance between the ray source and the detector (SDD) and the distance between the ray source and the rotation center (SOD), the ratio of the two affects the distance between the objects in the image, the measurement of SOD and SDD may cause measurement error, resulting in the distance between the objects in the image and the real life object does not match, so the ratio of the two needs to be determined. In the experiment, SDD is the theoretical value, SOD is the adjustable parameter, which is used to determine the ratio of the two. Through the analysis, it is found that the cone beam rotation center parameter and the SOD parameter are particularly important for the image reconstruction accuracy. The previous method mainly uses a general calibration template to collect the projection data of each marker point on the detector, and uses the spatial analytic geometry algorithm to solve the geometric parameters by solving the equation set of the cone beam CT system equation, the equation of the line connecting the ray source exit point and the marker point on the calibration template. In the method, the least square method is used to determine the center position of each projection marker point on the calibration template, but due to the instability of the least square method, it is easy to be affected by the extreme abnormal point, and the rotation center and SOD parameter obtained by the least square method can reach the graduation level, but it is still not accurate enough. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a high-precision calibration cone beam CT rotation center and SOD phantom method.

[0005] In order to solve the above technical problems, the present application discloses a high-precision calibration cone beam CT rotation center and SOD phantom method, comprising the following steps:

[0006] Step 1, constructing a calibration environment, including: setting a ray source and a detector; preliminarily determining the distance SOD from the ray source to the rotation center, the straight line distance SDD from the ray source to the detector and other conventional parameters.

[0007] Step 2, correcting the conventional geometric parameters using the conventional method, specifically including:

[0008] A calibration template is placed between the ray source and the detector, projection data of each mark point on the calibration template on the detector is collected, and the traditional geometric parameters are solved by using a spatial analytic geometry algorithm and by solving an equation set obtained by combining a cone beam CT system equation and a line equation of a connecting line between a ray source exit point and a mark point on the calibration template.

[0009] The traditional geometric parameters at least include a flat panel rotation angle error, a rotation center, a ray source to detector distance SDD, and a ray source to rotation center distance SOD.

[0010] Step 3, a steel needle phantom is made and added to the calibration environment, and specifically includes:

[0011] The steel needle phantom is set for calibration, and the ray source center, the steel needle phantom center and the detector center are arranged on a straight line.

[0012] The steel needle phantom includes: steel needles with the same diameter are arranged in a cross or a straight line at equal intervals in a transparent box.

[0013] The transparent box is made of synthetic resin.

[0014] Step 4, the traditional geometric parameters are analyzed, and important geometric parameters, i.e., the rotation center and the ray source to rotation center distance SOD, are selected.

[0015] Step 5, a traditional FDK algorithm is used to perform image reconstruction using the corrected traditional geometric parameters in step 2.

[0016] Step 6, the reconstructed image is judged, and if it meets the conditions, it enters step 7, otherwise the rotation center is fine-tuned and step 5 is repeated.

[0017] The reconstructed image is judged, i.e., whether the reconstructed image meets the cross-sectional characteristics and the center is distortion-free.

[0018] Step 7, the center distance between the steel needles in the steel needle phantom in the reconstructed image is calculated, if the threshold condition is not met, the ray source to rotation center distance SOD is fine-tuned, step 5 is re-executed, otherwise the calibration is ended.

[0019] The threshold condition is met, i.e., the distance between the steel needles in the reconstructed image is calculated, the difference between the distance and the actual distance between the steel needles is compared, and after the ray source to rotation center distance SOD is fine-tuned, the calculated difference is no longer increased, which is the threshold condition.

[0020] Advantages:

[0021] 1, the least square method used in the traditional method is easily affected by outliers, resulting in a large error in the estimated value, and the present application can simply and efficiently calibrate the error.

[0022] 2, the present application can analyze and compare different methods of existing CT geometry calibration, compare the applicability of different methods, and on this basis, reduce the calibration error of different methods, improve the precision, and have strong applicability.

[0023] 3, the method is simple and efficient, the phantom is simple and convenient to make, and the cost is low, the algorithm improvement caused by traditional phantom is reduced, and time and effort are saved. BRIEF DESCRIPTION OF DRAWINGS

[0024] The above and / or other aspects of the present application will become more apparent by describing in detail the preferred embodiments thereof with reference to the attached drawings.

[0025] Figure 1 It is a schematic diagram of the overall process of the present application.

[0026] Figure 2 It is a schematic diagram of the steel needle phantom.

[0027] Figure 3 It is a schematic diagram of the structure of the cone beam CT system and the definition of the coordinate system.

[0028] Figure 4 It is a schematic diagram of the steel needle section obtained by using traditional method and traditional geometric parameters and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the present application.

[0029] Figure 5 It is a comparison diagram of the results of traditional method calibration and high-precision calibration of CT rotation center and SOD.

[0030] Figure 6 It is a comparison diagram of the results of traditional method calibration and high-precision calibration of CT rotation center. DETAILED DESCRIPTION

[0031] The present application is based on the traditional calibration method, and a high-precision calibration phantom method for calibrating the rotation center and SOD of the cone beam CT is proposed, which further improves the parameter calibration precision. The present application initially uses the traditional method to calibrate the CT geometric parameters, after the calibration is completed, the steel needle phantom is used for CT scanning, image reconstruction, and post-processing is performed on the reconstructed image, the rotation center and the distance from the radiation source to the rotation center (SOD parameter) are continuously adjusted, so that the imaging section of the steel needle obtained is small, which meets the characteristics of the steel needle section, the center area is not distorted, and the distance between the steel needles meets the actual steel needle spacing.

[0032] A high-precision calibration phantom method for calibrating the rotation center and SOD of the cone beam CT, as shown in Figure 1 The specific steps are as follows:

[0033] Step one, constructing calibration environment, i.e. determining experimental data acquisition environment: the distance from the ray source to the rotation center is 420mm, the straight line distance from the ray source to the detector is 640mm, the detector element size is 0.25mm, the detector resolution is 768*768, the sampling interval is about 0.5 degrees, one pixel is stored by 4 bytes, and therefore the CT projection data size is about 720*768*768.

[0034] Step two, using the traditional method to calibrate, selecting the traditional general calibration template (reference: Analytic method based on identification of ellipse parameters for scanner calibration in cone beam tomography), collecting the projection data of each marker point on the detector, using the spatial analytic geometry algorithm, combining the equations of the cone beam CT system detector, the line method of the ray source exit point and the marker point on the calibration template, pre-correcting the machine with simple geometric parameters, and the parameter deviation is mainly composed of the detector column rotation angle Φ around the center, the detector row rotation angle θ around the center, the detector rotation angle η around the center, the detector movement ΔU along the row direction, the detector movement ΔV along the column direction, the actual distance SOD from the ray source to the rotation center real and the distance SDD from the ray source to the flat panel plane. real The important geometric parameters are analyzed, the important geometric parameters are calibrated with high precision, and it is found that the ratio of the parameters SDD real and SOD real will affect the image magnification, and the influence on the resolution after image reconstruction is not significant, so the experiment only considers one parameter SOD. The detector column rotation angle Φ around the center and the detector row rotation angle θ around the center have little effect on the resolution of the reconstructed image, but when the detector rotation angle around the center point has a slight deviation, it will cause the reconstructed image to have serious artifacts and deformation, and when the detector has errors along the row and column, it will cause the image to have artifacts after reconstruction. The experiment uses the traditional calibration method to calibrate the detector column rotation angle Φ around the center, the detector row rotation angle θ around the center and the detector rotation angle η around the center. Therefore, the experiment does not consider the angle error and the parameter SDD.

[0035] The experiment only considers high-precision calibration of the SOD parameter and the detector deviation along the row and column. The experiment uses the rotation center obtained by the traditional method to initially calibrate the detector deviation along the row and column, and then fine-tunes it using the method of the application. The experiment takes the ratio of the theoretical values of SDD and SOD as the initial value, and then fine-tunes SOD using the method of the application to control the ratio of the two, compares the actual distance with the distance between the objects displayed by the reconstructed image, and finally determines the SOD value.

[0036] Step three, image morphological processing and threshold segmentation are performed on the reconstructed image obtained by using the traditional calibration method. The threshold segmentation method used in this paper is the maximum inter-class variance method, i.e. using the gray level characteristics of the image, the image is divided into background and target two parts. The greater the inter-class variance between the background and the target, the greater the difference between the two parts constituting the image. When part of the target is misclassified as background or part of the background is misclassified as target, the difference between the two parts will become smaller. Using this method, the image threshold and the image edge region can be well determined.

[0037] Step four, after determining the image edge, the mean method is used to determine the center position of each steel needle image.

[0038] Step five, after observing the reconstructed steel needle object, if the imaging section of the steel needle is relatively small and the edge imaging conforms to the steel needle section characteristics, and there is no distortion in the center, it means that the initial rotation center conforms to the rotation center value determined by us. If the edge of the steel needle is blurred and irregular, and there is obvious distortion in the center, at this time, we need to continuously fine-tune the size of the rotation center until the steel needle imaging section is small, conforms to the section characteristics, and the center is not distorted. Finally, we determine the rotation center.

[0039] Step six, after determining the rotation center, the distance between the steel needles is calculated, and the actual distance between the steel needle models is compared. If the difference is too large, the SOD size is fine-tuned, and then the image is reconstructed to obtain the center position of the steel needle, calculate the distance between the steel needles, and compare the actual distance between the steel needle models. The difference between the actual and reconstructed steel needle images is continuously reduced until the SOD reaches the critical point (both increasing and decreasing will make the difference larger), and the process is ended.

[0040] Embodiment:

[0041] A simple phantom method for calibrating the rotation center and SOD of cone beam CT with high precision is as follows:

[0042] The traditional correction method used in this paper and the geometric calibration phantom reference (Analytic method based on identification of ellipse parameters for scanner calibration in cone beam tomography) mainly estimate the flat plate rotation angle error, rotation center, SDD and SOD. The projection data obtained in the article is used to determine the elliptical center position of each projection coordinate by using the least square method, obtain the coordinate data of the template mark point on the detector for calibration, and obtain the angle information, rotation center, and SOD and SDD ratio information through the coordinate data.

[0043] The cone beam CT experimental platform used in the specific implementation is an x-ray tomography measurement machine. The diameter of the focal point ray source is 4 um, the tube voltage is 200 kV, and the tube power is 0.5 mA. The cone beam CT system mainly includes a ray source system, a measured object, a detector system, a mechanical scanning system, a control system, a data acquisition and transmission system, and an image processing system. In the experiment, a steel needle phantom is used to calibrate the CT rotation center and the SOD measurement process:

[0044] As shown in Figure 2 , the steel needles with a diameter of 0.3 mm are arranged in a cross or a straight line at equal intervals in an arbitrary box made of transparent synthetic resin, as shown in Figure 3 , the steel needle phantom used for calibration is placed horizontally on the turntable of the cone beam CT system. The centers of the ray source, the steel needle phantom, and the detector should be as close to a straight line as possible. The distance from the ray source to the rotation center is 420 mm, the straight-line distance from the ray source to the detector is 640 mm, the size of the detector element is 0.25 mm, the resolution of the detector is 768*768, the sampling interval is about 0.5 degrees, one pixel is stored using 4 bytes, and therefore the size of the CT projection data is about 720*768*768.

[0045] Using the collected steel needle projection data combined with angle information, the rotation center, and the SOD and SDD ratio information, the FDK algorithm is used to reconstruct a three-dimensional steel needle image. The experiment calibrates the parameters according to the steel needle cross-sectional image. The FDK algorithm scans the measured object along a circular trajectory, and the projection images corresponding to different angles are obtained by rotating at equal intervals for one revolution. Through the conditions of accurate reconstruction, it can be known that the reconstruction of the central plane belongs to accurate reconstruction. If the reconstructed layer deviates from the central plane far away, the image obtained by reconstruction will have serious artifacts. Generally, when the cone angle is less than 5 degrees, the accuracy of the reconstructed image is higher. Therefore, under the condition of a small cone angle, the FDK algorithm has high reconstruction efficiency and is widely used. In this experiment, the cone angle is 4.5 degrees.

[0046] The three-dimensional steel needle image is reconstructed, the steel needle image in the cross-sectional direction is subjected to morphological processing and threshold segmentation, and it is observed whether the steel needle cross section conforms to the actual situation, that is, the center is not distorted, and the edge of the steel needle is clear and regular. Through the steel needle cross section, the rotation center is adjusted larger or smaller, and the image is reconstructed again using the FDK algorithm until the steel needle cross section conforms to the actual situation. In order to make the interval of the reconstructed image conform to the actual situation, the SOD is adjusted larger or smaller, so that the distance between the steel needles (pixel*element size) obtained by reconstruction conforms to the distance between the steel needles placed in the experiment. In the experiment, the actual distance between the steel needles is 10 mm.

[0047] As shown in Figure 4As shown, the steel needle section obtained by using traditional geometric parameters by the traditional method and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the application are compared. The first picture is the steel needle section picture reconstructed by using the traditional geometric parameters, and the second picture is the steel needle section picture obtained by high-precision calibration of the CT rotation center and SOD.

[0048] As shown, the steel needle section obtained by using traditional geometric parameters by the traditional method and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the application are compared. The first picture is the steel needle section picture reconstructed by using the traditional geometric parameters, and the second picture is the steel needle section picture obtained by high-precision calibration of the CT rotation center and SOD. Figure 5 As shown, the steel needle section obtained by using traditional geometric parameters by the traditional method and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the application are compared. The first picture is the steel needle section picture reconstructed by using the traditional geometric parameters, and the second picture is the steel needle section picture obtained by high-precision calibration of the CT rotation center and SOD.

[0049] As shown, the steel needle section obtained by using traditional geometric parameters by the traditional method and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the application are compared. The first picture is the steel needle section picture reconstructed by using the traditional geometric parameters, and the second picture is the steel needle section picture obtained by high-precision calibration of the CT rotation center and SOD. Figure 6 As shown, the steel needle section obtained by using traditional geometric parameters by the traditional method and the high-precision calibrated CT rotation center and SOD steel needle section proposed by the application are compared. The first picture is the steel needle section picture reconstructed by using the traditional geometric parameters, and the second picture is the steel needle section picture obtained by high-precision calibration of the CT rotation center and SOD.

[0050] In the specific implementation, the application provides a computer storage medium and a corresponding data processing unit, wherein the computer storage medium can store a computer program, and the computer program can run the invention content of the body method for high-precision calibration of the cone beam CT rotation center and SOD and part or all steps in each embodiment of the application when executed by the data processing unit. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), or the like.

[0051] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the application can be realized by means of a computer program and its corresponding general hardware platform. Based on such understanding, the technical solutions in the embodiments of the application can be embodied in the form of a computer program, i.e., a software product, which can be stored in a storage medium and includes a plurality of instructions for causing an equipment (which can be a personal computer, a server, a single-chip microcomputer, a MUU, or a network device) containing a data processing unit to execute the method described in each embodiment or some parts of the embodiments of the application.

[0052] The application provides a phantom method for calibrating a rotation center and SOD of a cone beam CT with high precision, and the method and approach for realizing the technical scheme are various, and the above description is only the preferred embodiment of the application, and it should be pointed out that, for the ordinary skilled in the art, some improvements and refinements can be made without departing from the principle of the application, and the improvements and refinements should also be regarded as the protection scope of the application. The components not explicitly described in the embodiment can be realized by the prior art.

Claims

1. A phantom method for high precision calibration of cone beam CT rotation center and SOD, characterized in that, The method comprises the following steps: Step 1, constructing a calibration environment; Step 2, correcting traditional geometric parameters using a traditional method, specifically including, placing a calibration template between a ray source and a detector, collecting projection data of each mark point on the calibration template on the detector, and using a spatial analytic geometry algorithm to solve the traditional geometric parameters by simultaneously solving a set of equations obtained from a cone beam CT system equation and a line equation of a connecting line between a ray source exit point and a mark point on the calibration template; the traditional geometric parameters at least include a flat panel rotation angle error, a rotation center, a ray source to detector distance SDD, and a ray source to rotation center distance SOD; Step 3, making a steel needle phantom and adding it to the calibration environment, specifically including, setting a steel needle phantom for calibration, and setting a ray source center, a steel needle phantom center, and a detector center on a straight line; the steel needle phantom comprises cross-distributed or linearly distributed steel needles with the same diameter at equal intervals in a transparent box; the transparent box is made of synthetic resin; Step 4, analyzing the traditional geometric parameters and selecting important geometric parameters; the important geometric parameters are the rotation center and the ray source to rotation center distance SOD; Step 5, using a traditional FDK algorithm to perform image reconstruction using the corrected traditional geometric parameters in Step 2; performing image morphological processing and threshold segmentation on the reconstructed image; the threshold segmentation method is a maximum inter-class variance method, that is, using the gray characteristics of the image, the image is divided into background and target two parts to determine the image edge; after determining the image edge, the mean value method is used to determine the center position of each steel needle image; Step 6, judging the reconstructed image; if it meets the conditions, it enters Step 7, otherwise, the rotation center is fine-tuned and Step 5 is repeated; the judgment of the reconstructed image is whether the reconstructed image meets the cross-sectional characteristics and the center is distortion-free; Step 7, calculating the distance between the steel needle centers in the steel needle phantom in the reconstructed image; if the threshold condition is not met, the ray source to rotation center distance SOD is fine-tuned, Step 5 is re-executed, otherwise the calibration is ended; the threshold condition is met, that is, the distance between the steel needles in the reconstructed image is calculated, and the difference between the distance and the actual distance between the steel needles is compared; after fine-tuning the ray source to rotation center distance SOD, if the calculated difference no longer increases, it is considered that the threshold condition is met.

2. The phantom method for high-precision calibration of cone-beam CT rotation center and SOD of claim 1, wherein, the construction of the calibration environment in Step 1 comprises setting a ray source and a detector; preliminarily determining a ray source to rotation center distance SOD, a ray source to detector straight line distance SDD, a flat panel rotation angle error, and a rotation center.

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