JP7656486B2 - Image file management system, method, and X-ray CT apparatus - Google Patents

Description

The present invention relates to an image file management system, in particular an image file management system for industrial X-ray CT devices.

Industrial X-ray CT scanners can measure the internal state of a test object non-destructively without cutting it, and are therefore used for many applications, including observing the internal structure of objects, detecting defects and foreign objects, measuring shapes, comparing shapes, and evaluating density.

In industrial X-ray CT equipment, the test object is placed between the X-ray source and the X-ray detector, and is rotated on a turntable. The detector measures the amount of X-rays that pass through the test object after they are attenuated as they pass through the test object. An image of the inside of the test object is reconstructed from the distribution of the amount of X-rays that pass through.

X-ray sources are used for industrial purposes, unlike medical applications, and the test objects are often metal industrial products, so X-ray energy with stronger penetrating power is required compared to the human body. X-ray tubes can be used up to 800 kV as an X-ray source to generate X-rays, but for energy levels in the MV range, an X-ray source using a linear accelerator is required.

Detectors used include area detectors such as image intensifiers and flat panels, as well as line detectors. Scanning methods include translation-rotation scanning mode (second generation scanning method) and rotation scanning mode (third generation scanning method), and the imaging area, scanning time, and image resolution differ depending on the scanning method. In addition, there are image reconstruction algorithms corresponding to each scanning method.

To use such an industrial X-ray CT device, it is necessary to understand the characteristics of each component device and set imaging conditions appropriate for the imaging purpose and the information on the test object. Related prior art documents include Patent Document 1.

JP 2007-178227 A

As mentioned above, finding the imaging conditions appropriate for the different imaging purposes and test objects for each shot can require repeated trial and error, which is often time-consuming. In addition, operators have different knowledge and different criteria for determining imaging conditions, which can result in inconsistent image quality.

The present invention aims to provide an image file management system and method, as well as an X-ray CT device, that can easily provide imaging conditions by integrating a database that centrally manages the accumulated image data of previously captured images with the performance parameter sheet of the device and inputting the imaging purpose and information on the test subject.

In order to achieve the above object, the present invention provides an image file management system having an electron beam accelerator that emits pulsed X-rays with a repetitive cycle, a scanner that drives a test object to be irradiated with the X-rays, a plurality of X-ray sensors that detect the X-rays irradiated to and passing through the test object, a signal processing device that processes an output signal of the X-ray sensor, an image reconstruction device that reconstructs a CT image using the output signal, a slice thickness variable mechanism that changes the cross-sectional thickness direction of the reconstructed CT image, a control device that controls the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device, a data collection device that converts the output signal into a digital signal and transfers it to the control device, and a management terminal that manages the CT images and imaging conditions stored in the image reconstruction device, the image file management system compares input information, which is the imaging purpose and test object information from an imaging request source, the CT images and the imaging conditions stored in the image reconstruction device, and a performance parameter sheet obtained from the image analysis results of shooting a standard test piece in the image file management system , and outputs imaging conditions suitable for the input information.

In order to achieve the above object, the present invention provides an image file management method for a system having an electron beam accelerator that emits pulsed X-rays with a repetitive cycle, a scanner that drives a test object to be irradiated with the X-rays, a plurality of X-ray sensors that detect the X-rays irradiated to and passing through the test object, a signal processing device that processes an output signal from the X-ray sensor, an image reconstruction device that reconstructs a CT image using the output signal, a slice thickness variable mechanism that changes the cross-sectional thickness direction of the reconstructed CT image, a control device that controls the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device, a data collection device that converts the output signal into a digital signal and transfers it to the control device, and a management terminal that manages the CT images and imaging conditions stored in the image reconstruction device, in which the management terminal reads input information, which is the imaging purpose and test object information from an imaging request source, the CT images and the imaging conditions stored in the image reconstruction device, and compares them with an accumulation database that centrally manages them, and a performance parameter sheet obtained from an image analysis result of shooting a standard test piece in the system , and outputs imaging conditions suitable for the input information.

Furthermore, in order to achieve the above object, the present invention provides an electron beam accelerator that emits pulsed X-rays at a repetitive cycle, a scanner that drives a test object onto which the X-rays are irradiated, a plurality of X-ray sensors that detect the X-rays that are irradiated onto and pass through the test object, a signal processing device that processes the output signal of the X-ray sensor, an image reconstruction device that reconstructs a CT image using the output signal, a slice thickness variable mechanism that changes the cross-sectional thickness direction of the reconstructed CT image, and a control device that controls the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device. The X-ray CT device has a data collection device that converts the output signal into a digital signal and transfers it to the control device, and a management terminal that manages the CT images and imaging conditions stored in the image reconstruction device, and the management terminal reads input information from the imaging request source, which is the imaging purpose and test subject information, the CT images and the imaging conditions stored in the image reconstruction device, and compares them with a centrally managed accumulation database and a performance parameter sheet obtained from the image analysis results of taking images of a standard test piece with the X-ray CT device, and outputs imaging conditions suitable for the input information.

From a wide variety of industrial X-ray CT devices, the imaging conditions suitable for the diverse imaging purposes and test objects can be easily set in a short time and without relying on the operator, ensuring the quality of the CT images after imaging.

1 is a diagram illustrating a configuration example of an industrial X-ray CT apparatus according to a first embodiment. FIG. 2 is a diagram showing a screen of a CT image management system managed on a management terminal. 13 is a flowchart of a collation function of the CT image management system. FIG. 11 is a diagram showing parameters to be input into a CT image management system. FIG. 11 is a diagram showing parameters to be input into a CT image management system. This is an accumulation database of the CT image management system. FIG. 1 is a diagram showing a performance parameter sheet of a CT image management system. FIG. 1 is a diagram showing a performance parameter sheet of a CT image management system. FIG. 1 is a diagram showing a performance parameter sheet of a CT image management system. 11 is a collation flowchart of the CT image management system when the imaging purpose is internal observation. 11 is a comparison flowchart of the CT image management system when the imaging purpose is defect/foreign object detection. 11 is a comparison flowchart of the CT image management system when the imaging purpose is shape measurement. 11 is a comparison flowchart of the CT image management system when the imaging purpose is shape comparison. 13 is a comparison flowchart of the CT image management system when the imaging purpose is density evaluation. 11 is a diagram showing an example of a comparison result of imaging conditions obtained by the CT image management system. FIG.

Below, an embodiment of the present invention is explained with reference to the drawings.

Figure 1 is a diagram showing one configuration of an X-ray CT device according to the first embodiment. The X-ray CT device 100 of this embodiment is an industrial X-ray CT device having the structure of an X-ray CT device equipped with multiple scanning methods, mainly the third generation method.

The X-ray CT device 100 includes an electron beam accelerator 1 that outputs an X-ray fan beam 2, a scanner 3 that is a turntable on which a test object 10 is placed, a collimator 5 that suppresses the incidence of scattered X-rays on the X-ray sensors 4 to improve the S/N ratio of the multiple X-ray sensors 4 that detect X-rays that have passed through the test object 10, a slice thickness variable mechanism 6 that changes the CT section thickness direction, a signal processing device 7 that converts the output signal of the X-ray sensor 4 into a current-voltage signal and amplifies it, a data collection device 8 that converts an analog signal from the signal processing device 8 into a digital signal and collects digital data, a control device 11 that controls the entire X-ray CT device 100, including the electron beam accelerator 1, the scanner 3, and the signal processing device 8, an image reconstruction device 12 that reconstructs CT images, an image analysis device 21 that performs image analysis of CT images according to the purpose of shooting, and a management terminal 22 that centrally manages past CT image data groups.

The control device 11 is, for example, a personal computer consisting of a main body incorporating a liquid crystal display device, input means such as a keyboard and a mouse, a storage device, a CPU and its peripheral circuits, memory, etc., and allows an operator to input imaging conditions. The electron beam accelerator 1 is connected to the control device 11 by a control cable 31, and the generation and stopping of the X-ray fan beam 2 is controlled by the control device 11.

The scanner 3 has a rotation function for rotating the test object 10 to change the cross-sectional direction for CT imaging, as well as a function for moving the test object 10 up and down to perform cross-sectional imaging at each height of the test object 10. The scanner 3 is connected to the control device 11 by a control cable 32, just like the electron beam accelerator 1, and the rotation and vertical position of the scanner 3 are adjusted. Rotation angle position information and vertical position information of the scanner 3 are output to the control device 11. The slice thickness variable mechanism 6 is connected to the control device 11 by a control cable 34, and the CT cross-sectional thickness direction is controlled by the control device 11.

The X-ray sensors 4 are arranged in a row so that they can see the point where the X-ray fan beam 2 is generated. The more X-ray sensors 4 there are, the higher the resolution of the CT image, and in this embodiment, 1024 are installed. In FIG. 1, the X-ray sensors 4 are represented as 4-1 to 4-1024, and any one of the X-ray sensors is represented as 4-n. The X-ray sensor 4 detects the X-rays that have passed through the test object 10 each time the X-ray fan beam 2, which is a pulse in time, is output from the electron beam accelerator 1 at a fixed rotation angle of the scanner 3 in synchronization with the rotation of the scanner 3.

The output signal from each X-ray sensor 4, which corresponds to the amount of X-rays incident on each X-ray sensor 4, is converted from a current signal to a voltage signal by the signal processing device 7 and then amplified. The voltage signal is output to the data collection device 8 via the signal cable 35, and is converted to a digital signal by the data collection device 8. The digital signal is sent to the image reconstruction device 12 via the communication cable 30, the control device 11, and the communication cable 36, and the CT image is reconstructed by the image reconstruction device 12. The image reconstruction device 12 stores an attribute file that records information on the imaging conditions along with the CT image data.

In the X-ray CT device 100 using the electron beam accelerator 1, X-rays are usually pulsed X-rays that are generated periodically due to the characteristics of the electron beam accelerator 1. Generally, a strong X-ray pulse (a collection of X-ray photons) with a width of 5 μs is output from the electron beam accelerator 1 at a period of 3.3 ms. In this embodiment, the X-ray pulse is irradiated and measured 3000 times on the test object 10 during one rotation of the test object 10. In other words, the X-ray sensor 4 measures the X-ray amount every 0.12 degrees in the rotation angle of the scanner 3. Since there are 1024 X-ray sensors 4, the amount of data required to reconstruct one slice is 1024 x 3000 pieces of data.

The CT image data generated and stored by the image reconstruction device 12 is sent via a communication cable 37 to an image analysis device 21 such as a computer, where the CT image is analyzed.

Figure 2 shows an example screen of the CT image management system 23 managed on the management terminal 22. The imaging data information 25 (attribute file) stored in the image reconstruction device 12 is read by the management terminal 22 via the communication cable 39, and is displayed as a list on the CT image management system 23. The main menu 24 has a function to display images from the accumulated imaging data information 25, a function to convert images to bmp, JPEG, etc., and a comparison function to derive imaging conditions for new imaging.

Figure 3 is a flowchart of the comparison function of the CT image management system 23. For new imaging information, the imaging purpose and imaging specimen information are input as input parameters. The reference data to be compared is an accumulation database based on past imaging data information 25 and a performance parameter sheet that has been previously obtained by imaging a standard test piece and performing CT image analysis. The CT image management system 23 compares the two and outputs the optimization conditions to the control device 11.

Figures 4A and 4B are lists of input parameters, with the imaging purpose shown on the top and the specimen shown on the bottom. The imaging purpose, which is one of the input parameters, is classified into "internal observation," which aims to visualize the internal information of the test specimen and observe the internal structure; "defect/foreign body detection," which aims to detect the shape and size of defects such as blowholes, cracks, and peeling and foreign bodies present inside the test specimen; "shape measurement," which aims to measure the internal shape, such as distance, angle, curvature, and volume, on CT images, which is difficult to measure using destructive testing; "shape comparison," which aims to compare shape differences by comparing CT images or CT data and design data such as CAD data; and "density evaluation," which aims to visualize the separation of different materials and density changes from CT images of test specimens made of composite materials.

The objectives are divided into sub-categories: for "internal observation," the "target range (1mm to 1000mm),""target size (0.5mm to 1000mm)," and "target material (from soft materials such as resin to high-density materials such as iron)" to be observed within the dimensions of the test object; for "defect and foreign object detection," the "detection range (1mm to 1000mm),""detection size (0.5mm to 1000mm)," and "detection material (from soft materials such as resin to high-density materials such as iron)" to be detected within the dimensions of the test object; and for "shape measurement," the "target range (0.5mm to "Shape comparison" is divided into "Comparison object (another CT data or design data such as CAD data)" which is compared with the CT data of the test piece, "Comparison accuracy (0.01mm to 0.2mm)" and "External factors (stress, heat, pressure, chemical changes, etc.)"; and "Density evaluation" is divided into "Target range (1mm to 1000mm),""Target size (0.5mm to 1000mm)" and "Density difference (0.2g/ ^cm3 to 10g/ ^cm3 )" to be evaluated within the dimensional size of the test piece.

The other input parameter, the imaged specimen, i.e., information on the test specimen, is classified into "specimen name (e.g., cylinder head A1)," which indicates the product name or part name (if there is an identifying number, it is added), "number (from 1 to several tens)," which indicates the number of test specimens to be photographed, "shape (width 500 mm, depth 500 mm, height up to 1000 mm)," which indicates the internal dimensions of the test specimen, "material (soft materials such as resin to high-density materials such as iron)," which indicates the material of the material and parts that make up the test specimen, and "mass (1 kg to 100 kg)," which indicates the mass of each test specimen.

Figure 5 is a list of the accumulation database. The accumulation database collects imaging data information and classifies it into the following: "File name" which is the directory name, "Shooting date" which indicates the date when the image was taken, "Shooting time" which indicates the start and end time when the image was taken, "Shooting conditions" which indicates the conditions when the image was taken, "Shooting purpose" which indicates the purpose of the image, and "Photographed specimen" which indicates information about the test subject to be photographed.

"Photographing conditions" are further subdivided into "X-ray energy (1MeV, 6MeV, 9MeV)", "scanning method (3rd generation, 2nd generation, Hi-Brid method)", "image size (1500 x 1500, etc.)", "pixel size (0.2mm/pixel, 0.3mm/pixel, 0.4mm/pixel)", "slice thickness (0.4mm, 0.5mm, 1.0mm)", "photographing position (0mm to 1000mm)", "photographing interval (0.1mm to 1000mm)", and "number of photographs (1 to 10000)". "Photographing purpose" is classified in the same way as the photographing purpose of the input data, and "Photographed specimen" is classified in the same way as the test subject information of the input data.

Figures 6A, 6B, and 6C are tables listing performance parameter sheets. As shown in Figure 6A, the performance parameter sheet classifies the following: "effective spatial resolution," which indicates the smallest interval that can be spatially identified taking into account the amount of noise in the image; "shape extraction error," which indicates the difference between the actual dimensions and the shape extracted from the point cloud extracted from the CT image; "density (contrast) resolution," which indicates the limit density (contrast) at which different materials can be identified taking into account the amount of noise in the image; and "maximum transmission size," which indicates the thickness of a material that corresponds to the transmission distance when the lower limit of the measurement range of the detector system is reached.

Specific performance values of "(effective) spatial resolution" are shown in Fig. 6B, and specific performance values of "shape extraction error" are shown in Fig. 6C. Using Fig. 6A, Fig. 6B, and Fig. 6C, it is possible to provide indices for different combinations of X-ray energy, scanning method, slice thickness, and standard test piece (material and size) for each performance. For example, when the X-ray energy is 9 MeV, the scanning method is the third generation method (pixel size is 0.4 mm/pixel), the slice thickness is 1.0 mm, the material of the standard test piece is aluminum, and the size (diameter) of the standard test piece is 200 mm, the "(effective) spatial resolution" is 0.55 mm, the "shape extraction accuracy (error)" is 0.01 mm, the "density (contrast) resolution" is 0.1 g/cm ³ , and the maximum transmission size is 960 mm.

Figure 7A is a flowchart for deriving imaging conditions when the imaging purpose is "internal observation." For example, the input parameters for "internal observation" are "target range": height 50mm to 100mm, "target size": width 200mm, depth 200mm, "target material": iron. The input parameters for the imaging specimen information are "specimen name": housing, "quantity": 1, "shape": width 200mm, depth 200mm, height 100mm, "material": iron, "mass": 15kg.

For "internal observation," the necessary conditions are that the target size and target material are within the maximum transmission size of the performance parameter sheet in Figure 6A. Based on the performance parameter sheets in Figures 6A, 6B, and 6C, branching can be done from the input parameters, so branching occurs when the input parameter: target material density is equal to or greater than iron or equal to aluminum (S701). If it is equal to or greater than iron (YES), and the input parameter: target size is 200 mm or greater (YES in S702), the X-ray energy is set to 9 MeV based on the performance parameter sheet: transmission size (S704). If it is less than 200 mm, the X-ray energy is 6 MeV or 1 MeV. In this example, since the target size is 200 mm and the material is iron, the X-ray energy, which is one of the imaging conditions, can be determined to be 9 MeV. The same applies to the case of aluminum or less (S703, S705).

For the remaining imaging conditions, common conditions such as scanning method, slice thickness, and imaging intervals are extracted from the accumulated database based on the same imaging purpose and test object information, and from the most recent data, those that have been used frequently or have received high evaluation from the imaging requester are selected (S706). After obtaining the above flow (S707), the optimal imaging conditions can be displayed, for example, as an imaging condition matching result table as shown in Figure 8.

Figure 7B is a flowchart for deriving imaging conditions when the imaging purpose is "detection of defects and foreign objects." For example, the input parameters for "detection of defects and foreign objects" are "detection range": height 50mm to 100mm, "detection size": 0.4mm or less, and "target material": iron. The input parameters for the imaging specimen information are "specimen name": casting, "quantity": 1 piece, "shape": width 200mm, depth 200mm, height 200mm, "material": iron, and "mass": 25kg. For "detection of defects and foreign objects," the necessary conditions are that the detection size and target material are equal to or less than the effective spatial resolution of the performance parameter sheets in Figures 6A and 6B. Based on the performance parameter sheets in Figures 6A and 6B, branching can be done from the input parameters, so first, branching occurs when the input parameter: detection size is less than 0.5mm or 0.5mm or more (S711). If it is less than 0.5mm, the scanning method will be the Hi-Bird method (pixel size 0.2mm/pixel), the slice thickness will be 0.5mm, and the shooting interval will be 0.5mm or less, based on the performance parameter sheet: effective spatial resolution (S712). Next, the input parameter: the target material density will branch depending on whether it is equal to or greater than iron or equal to aluminum (S714). In this example, since the target size is 200mm wide (YES in S715), the X-ray energy will be 9MeV, based on the performance parameter sheet: transmission size (S717).

For the remaining imaging conditions, common imaging interval conditions are extracted from the accumulated database for the same imaging purpose and test specimen information, and from the most recent data, those that are frequently used or have received high evaluations from the imaging requesters are selected (S718). By obtaining the above flow, the optimal imaging conditions (S719) can be displayed as an imaging condition matching result table, as shown in Figure 8.

Figure 7C is a flowchart for deriving imaging conditions when the imaging purpose is "shape measurement." For example, the input parameters for "shape measurement" are "target range": height 10mm to 20mm, "measurement content": diameter, and "measurement accuracy": 0.01mm. The input parameters for the imaged specimen information are "specimen name": pipe, "quantity": 1 piece, "shape": width 100mm, depth 220mm, height 100mm, "material": iron, and "mass": 15kg.

For "shape measurement", a necessary condition is that the measurement accuracy must be equal to or less than the shape extraction accuracy in the performance parameter sheets in Figures 6A and 6C. Based on the performance parameter sheets in Figures 6A and 6C, branching can be done from the input parameters, so first, branching occurs based on whether the input parameter: target material density is equal to or greater than iron or equal to or less than aluminum (S721). If it is equal to or greater than iron, input parameters: target range is 200 mm or greater (YES in S722), and measurement accuracy is less than 0.1 mm (YES in S723). In this example, the target size is 220 mm and the measurement accuracy is 0.01 mm, so the X-ray energy is 9 MeV based on the performance parameter sheet: shape extraction accuracy (S724).

For the remaining imaging conditions, common conditions such as scanning method, slice thickness, and imaging intervals are extracted from the accumulated database based on the same imaging purpose and test object information, and from the most recent data, those that are frequently used or have received high evaluation from the imaging requester are selected (S726). By obtaining the above flow, the optimal imaging conditions (S727) can be displayed as an imaging condition matching result table as shown in Figure 8.

Figure 7D is a flowchart for deriving imaging conditions when the imaging purpose is "shape comparison." For example, the input parameters for "shape comparison" are "comparison target": CT data, "comparison accuracy": 0.01 mm, and "external factors": before and after thermal cycle test. The input parameters for imaging specimen information are "specimen name": tank, "quantity": 1, "shape": width 300 mm, depth 300 mm, height 1000 mm, "material": iron, and "mass": 30 kg. For "shape measurement," a necessary condition is that the measurement accuracy must be equal to or less than the shape extraction accuracy in the performance parameter sheets in Figures 6A and 6C.

Based on the performance parameter sheets of Figures 6A and 6C, the input parameters can be branched, so first, the input parameters: target material density is equivalent to or greater than iron or equivalent to aluminum (S731). If it is equivalent to or greater than iron, the input parameters: target range is 200 mm or greater (YES in S732), and the comparison accuracy is less than 0.1 mm (YES in S733). In this example, the target size is 300 mm and the comparison accuracy is 0.01 mm, so the X-ray energy is 9 MeV from the performance parameter sheet: shape extraction accuracy (S734). For the remaining imaging conditions, common conditions such as scanning method, slice thickness, and imaging interval are extracted from the accumulated database for the same imaging purpose and test specimen information, and from the most recent data, those that are frequently used or highly evaluated by the imaging requester are selected (S736). From the above flow, the optimal imaging conditions (S737) can be displayed as an imaging condition comparison result table shown in Figure 8.

7E is a flowchart for deriving imaging conditions when the imaging purpose is "density evaluation." For example, the input parameters for "density evaluation" are "target range": height 100 mm to 200 mm, "target size": diameter 100 mm, "density difference": 0.2 g/ ^cm3 . The input parameters for the imaging specimen information are "specimen name": motor, "number": 1 piece, "shape": diameter 150 mm, height 300 mm, "material": iron, "mass": 30 kg. In the case of "density evaluation," a necessary condition is that the density difference is equal to or less than the density resolution of the performance parameter sheet in FIG. 6A.

Based on the performance parameter sheet of FIG. 6A, the input parameters can be branched, so first, the input parameter: whether the target size is 10 mm or more or less than 10 mm is branched (S741). If it is 10 mm or more, the input parameters: density difference is 0.1 g/cm ³ or more (YES in S742), and the target material density is equivalent to or greater than iron (YES in S743). In this example, the target size is 100 mm in diameter and the density difference is 0.2 g/cm ³ , so the X-ray energy is 9 MeV from the performance parameter sheet: density resolution and maximum penetration size (S745). For the remaining imaging conditions, common conditions such as scanning method, slice thickness, and imaging interval are extracted from the accumulated database based on the same imaging purpose and test object information, and from the most recent data, those that are frequently used or highly evaluated by the imaging requester are selected (S747). By obtaining the above flow, the optimal imaging conditions (S748) can be displayed as an imaging condition comparison result table shown in FIG. 8.
According to the CT image management system of this embodiment, imaging conditions suitable for the imaging purpose and test subject information from the imaging requester can be easily derived, and these imaging conditions are sent to the control device 11 via the communication cable 39 and automatically entered, and CT images are acquired by the X-ray CT device 100, thereby reducing errors in condition input by the operator and achieving high quality in the resulting CT images and image analysis results.

As shown in FIG. 4B, in this embodiment, "design data (CAD data)" is added to the test subject information input in the CT image management system 23 in embodiment 1. Only the functions that have been changed from embodiment 1 are shown below.

The image management system 23 provides a method for placing the test specimen 10 suitable for the imaging purpose on the turntable, taking into consideration the maximum transmission path and the direction that is easy to place on the turntable surface, based on the "design data (CAD data)" of the imaging specimens in the input parameters of Figure 4B.

The CT image management system of this embodiment can easily derive imaging conditions and subject installation methods suited to the imaging purpose and subject information provided by the imaging requester, thereby shortening imaging preparation and imaging time.

The present invention is not limited to the above-described embodiments and modifications, and further includes various modifications. For example, the above-described embodiments and modifications have been described in detail to clearly explain the present invention, and are not necessarily limited to those having all of the configurations described.

REFERENCE SIGNS LIST 1 Electron beam accelerator 3 Scanner 4 X-ray sensor 6 Slice thickness variable mechanism 10 Test object 11 Control device 12 Image reconstruction device 21 Image analysis device 22 Management terminal 23 CT image management system 24 Main menu 25 Imaging data information 100 X-ray CT device

Claims (15)

an image file management system comprising: an electron beam accelerator which emits pulsed X-rays at a repetitive cycle; a scanner which drives a test object onto which the X-rays are irradiated; a plurality of X-ray sensors which detect the X-rays which are irradiated onto and pass through the test object; a signal processing device which processes an output signal from the X-ray sensor; an image reconstruction device which reconstructs a CT image using the output signal; a slice thickness variable mechanism which changes a cross-sectional thickness direction of the reconstructed CT image; a control device which controls the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device; a data collection device which converts the output signal into a digital signal and transfers it to the control device;
Read input information, which is the imaging purpose and test subject information from the imaging requester, the CT images stored in the image reconstruction device, and the imaging conditions, compare them with a centrally managed accumulation database and a performance parameter sheet obtained from the image analysis results of photographing a standard test piece in the image file management system , and output imaging conditions suitable for the input information.
1. An image file management system comprising:
2. The image file management system according to claim 1,
The performance parameter sheet includes an effective spatial resolution as a performance parameter.
1. An image file management system comprising: 2. The image file management system according to claim 1,
The performance parameter sheet includes a shape take-out error as a performance parameter.
1. An image file management system comprising: 2. The image file management system according to claim 1,
The performance parameter sheet includes density resolution as a performance parameter.
1. An image file management system comprising: 2. The image file management system according to claim 1,
The performance parameter sheet includes a maximum transmission size as a performance parameter.
1. An image file management system comprising: 2. The image file management system according to claim 1,
The imaging purpose includes internal observation for the purpose of visualizing internal information of the test object and observing the internal structure;
1. An image file management system comprising: 2. The image file management system according to claim 1,
The imaging purpose includes defect/foreign object detection for the purpose of detecting the shape and size of defects or foreign objects present inside the test object,
1. An image file management system comprising: 2. The image file management system according to claim 1,
The imaging purpose includes shape measurement for the purpose of performing various measurements on a CT image of the internal shape of the test object,
1. An image file management system comprising: 2. The image file management system according to claim 1,
The imaging purpose includes a shape comparison for comparing CT images with each other or CT data with design data to compare differences in shapes.
1. An image file management system comprising: 2. The image file management system according to claim 1,
The imaging purpose includes density evaluation for the purpose of visualizing different material separation and density change from the CT image of the test object,
1. An image file management system comprising: a control device for controlling the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device; a data collection device for converting the output signal into a digital signal and transferring the digital signal to the control device; and a management terminal for managing the CT images and imaging conditions stored in the image reconstruction device, wherein the management terminal reads input information, which is the imaging purpose and the object to be tested, from an imaging request source, and the CT images and the imaging conditions stored in the image reconstruction device, compares the input information with an accumulation database for unified management and a performance parameter sheet obtained from an image analysis result obtained by imaging a standard test piece in the system , and outputs the imaging conditions suitable for the input information.
23. An image file management method comprising:
12. The image file management method according to claim 11,
The performance parameter sheet includes an effective spatial resolution as a performance parameter.
23. An image file management method comprising: 12. The image file management method according to claim 11,
The performance parameter sheet includes a shape take-out error as a performance parameter.
23. An image file management method comprising: an X-ray CT apparatus comprising: an electron beam accelerator which emits pulsed X-rays at a repetitive cycle; a scanner which drives a test object onto which the X-rays are irradiated; a plurality of X-ray sensors which detect the X-rays which are irradiated onto and pass through the test object; a signal processing device which processes an output signal from the X-ray sensor; an image reconstruction device which reconstructs a CT image using the output signal; a slice thickness variable mechanism which changes the cross-sectional thickness direction of the reconstructed CT image; a control device which controls the electron beam accelerator, the scanner, the signal processing device, and the image reconstruction device; a data collection device which converts the output signal into a digital signal and transfers it to the control device;
The management terminal reads input information, which is the imaging purpose and test subject information from an imaging request source, and the CT images and imaging conditions stored in the image reconstruction device, compares them with a centrally managed accumulation database and a performance parameter sheet obtained from the image analysis results of photographing a standard test piece with the X-ray CT device, and outputs imaging conditions suitable for the input information.
An X-ray CT apparatus characterized by the above. 15. The X-ray CT apparatus according to claim 14,
The performance parameter sheet includes, as performance parameters, an effective spatial resolution and a shape extraction error.
An X-ray CT apparatus characterized by the above.

Images