Data processing methods and apparatus, CT equipment and storage media

Abstract

This application proposes a data processing method and apparatus, a CT device, and a storage medium. The method includes: acquiring first data including air region data, wherein the first data is image domain data or projection domain data; acquiring actual air values ​​based on the air region data in the first data, and determining a calibration value according to an air standard value and the actual air values; and correcting the data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or second data whose acquisition time meets a preset condition with the first data. The technical solution of this application utilizes the air data obtained from scanning as a calibration reference object to calibrate the scanning results corresponding to the scanned body, which can improve the accuracy of calibration and help obtain more accurate and reliable diagnostic images.

Description

[Technical Field]

[0001] This application relates to the field of computer technology, and in particular to a data processing method and apparatus, a CT device, and a storage medium. [Background Technology]

[0002] like Figure 1 As shown, a CT scanner gantry mainly consists of X-ray tubes and detectors placed opposite each other. The detectors are arranged in an arc, with their focal points located at the center of the circle, ensuring that the normal vector of each detector is aligned with the focal point of the X-ray tube. During scanning, the patient is at the center of the rotating gantry. The X-ray tubes and detectors, mounted on the gantry, rotate synchronously around the patient. The X-ray tubes emit X-rays, and the detectors periodically receive the X-rays passing through the patient and convert them into data signals for storage. In this way, thousands of acquisitions can be performed in one rotation of the X-ray tubes and detectors. Finally, based on the acquired data, image reconstruction can be performed to obtain the tomographic structure of the patient's internal structure as a diagnostic image.

[0003] To achieve high-quality diagnostic and treatment results, offline calibration is often used to correct the acquired data before image reconstruction. Specifically, offline calibration generates correction mapping coefficients, which are then used to correct the data. However, this offline calibration is based on the results of the previous CT scan. The intensity and spectrum of the radiation emitted by the X-ray tube inside the CT scanner change with the radiation time. The scintillator in the detector also experiences increased radiation damage due to the change in radiation time. Furthermore, the photodiodes in the detector are affected by ambient temperature. In short, many parameters within the CT scanner are constantly changing. Even if the interval between the previous and current CT scans is short, the actual CT parameters used in the two scans will differ. Therefore, using the previous CT scan as a benchmark to correct the data of the current scan will result in inaccurate correction, thus affecting the accuracy of the reconstructed diagnostic and treatment images and ultimately impacting the diagnostic and treatment outcomes.

[0004] Therefore, how to improve the effectiveness of CT scan result correction has become an urgent technical problem to be solved. [Summary of the Invention]

[0005] This application provides a data processing method and apparatus, a CT device, and a storage medium, aiming to solve the technical problem in the related art where inaccurate offline calibration of CT scan results affects the accuracy of reconstructed diagnostic images.

[0006] In a first aspect, embodiments of this application provide a data processing method, comprising: acquiring first data including air region data, wherein the first data is image domain data or projection domain data; acquiring actual air values ​​based on the air region data in the first data, and determining a calibration value based on an air standard value and the actual air values; and correcting the data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or second data whose acquisition time with the first data meets a preset condition.

[0007] Secondly, embodiments of this application provide a data processing apparatus, comprising: a first data acquisition unit, configured to acquire first data including air region data, wherein the first data is image domain data or projection domain data; a calibration value acquisition unit, configured to acquire actual air values ​​based on the air region data in the first data, and determine a calibration value according to an air standard value and the actual air values; and a correction processing unit, configured to correct data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or second data whose acquisition time with the first data meets a preset condition.

[0008] Thirdly, embodiments of this application provide a CT device, including: an internal bus, and a memory, a processor, and an external interface connected via the internal bus, wherein the external interface is used to connect to the detectors of the CT system, the detectors including multiple detector chambers and corresponding processing circuits; the memory is used to store computer-executable instructions corresponding to CT scanning logic; the processor is used to read the computer-executable instructions on the memory and execute the method described in the first aspect based on the computer-executable instructions.

[0009] Fourthly, embodiments of this application provide a storage medium storing computer-executable instructions for executing the method flow described in the first aspect above.

[0010] The above technical solution addresses the technical problem in related technologies where inaccurate offline calibration of CT scan results affects the accuracy of reconstructed diagnostic images. Firstly, it acquires first data, including air region data, which can be image domain data or projection domain data. The first data is data obtained from medical scanning processing, including but not limited to image domain data and projection domain data. The projection domain data reflects the attenuation of rays passing through the scanning body, while the image domain data reflects the grayscale differences at various scanning locations in the scanned image.

[0011] When a scanning device performs a scan, the scanning object typically does not fill the entire scanning channel. This means that the space outside the scanning object within the scanning channel is filled with air. Therefore, the data obtained when scanning the scanning object may include data about the air region, and the first data segment contains this air region.

[0012] Next, based on the air region data in the first data, the actual air value is obtained, and a calibration value is determined according to the air standard value and the actual air value. The air standard value refers to the value obtained by the scanning device scanning the air under predetermined parameters, while the actual air value refers to the value obtained by the scanning device scanning the air under the current parameters.

[0013] Since the scanning device can scan both the air area and the object being scanned, the air area can be used as a reference for calibrating the scanning results of the object. Specifically, the deviation between the actual air value and the standard air value can be identified as the deviation between the data to be calibrated obtained from the scanned object and the standard value of that data. Furthermore, the deviation between the actual air value and the standard air value is determined as a calibration value and used to calibrate the data to be calibrated.

[0014] Based on this, the data to be corrected is corrected based on the calibration value to obtain the target data.

[0015] If the data to be calibrated is the first data, since the scanning device scans both the air region and the scanning body under the current parameters, and the parameters used when scanning the air region and the scanning body are the same, the deviations in the corresponding data will also be the same. Based on this, the air region can be used as a reference object for calibrating the scanning results of the scanning body, thereby achieving real-time online calibration. Specifically, the deviation between the actual air value and the air standard value can be identified as the deviation between the data to be calibrated obtained by scanning the scanning body and the standard value of that data. Further, the deviation between the actual air value and the air standard value is determined as the calibration value and used to calibrate the data to be calibrated.

[0016] Therefore, by utilizing the consistency of parameters used by the scanning equipment to scan the air region and the scanned body in a single scan, and using the air data within a single scan as a calibration reference, the data to be calibrated on the scanned body is calibrated. In other words, the actual air values ​​of the current scan are used to correct the data of the scanned body in the current scan. This avoids the error caused by differences in scanning equipment parameters between different scans, improves the accuracy of calibration, and helps to obtain more accurate and reliable diagnostic images.

[0017] If the data to be corrected is the second data whose acquisition time meets the preset conditions as the first data, since the air region data of the first data is acquired online and the acquisition time meets the preset conditions as the second data, the contribution of air to the first data and the contribution to the second data are basically the same within the preset conditions. Therefore, the correction value obtained based on the air region data of the first data can be used as a reference object for correcting the second data. This avoids the error caused by the parameter differences of the scanning equipment between different scans on the calibration operation, improves the accuracy of calibration, and helps to obtain more accurate and reliable diagnostic images.

[0018] Therefore, using the air data obtained from the scan as a calibration reference to calibrate the scan results corresponding to the scanned body can improve the accuracy of the calibration and help obtain more accurate and reliable diagnostic images. [Attached Image Description]

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 A schematic diagram of the structure of a CT scanner gantry in the related technology is shown;

[0021] Figure 2 A flowchart of a data processing method according to an embodiment of this application is shown;

[0022] Figure 3 A flowchart of a data processing method according to another embodiment of this application is shown;

[0023] Figure 4 A flowchart of a data processing method according to another embodiment of this application is shown;

[0024] Figure 5 A flowchart of a data processing method according to another embodiment of this application is shown;

[0025] Figure 6 It shows Figure 5 A schematic diagram of the initial projection of the scanned patient in the data processing method shown;

[0026] Figure 7 It shows Figure 6 The graph shows the variation of projection values ​​corresponding to the initial CT image.

[0027] Figure 8 A flowchart of a data processing method according to yet another embodiment of this application is shown;

[0028] Figure 9 A block diagram of a data processing apparatus according to an embodiment of this application is shown.

Detailed Implementation Methods

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Example 1

[0031] Figure 2 A flowchart of a data processing method according to an embodiment of this application is shown.

[0032] like Figure 2 As shown, a data processing method according to an embodiment of this application includes:

[0033] Step 202: Obtain first data including air region data, wherein the first data is image domain data or projection domain data.

[0034] The first data consists of data obtained from medical scanning processes, including but not limited to image domain data and projection domain data. Projection domain data reflects the attenuation of the X-rays from the scanning device as they pass through the scanning body, while image domain data reflects the grayscale differences at various scanning locations in the image.

[0035] When a scanning device performs a scan, the scanning volume typically does not fill the entire scanning channel (i.e., the detector's detection channel is not completely occupied by the scanning volume). In other words, the space outside the scanning volume in the scanning channel is filled with air. The X-rays emitted by the X-ray tube pass through the air outside the scanning volume and are received by the detection channel, converting them into data. It is understandable that the initial data may include both scanning volume data and air region data.

[0036] Step 204: Based on the air area data in the first data, obtain the actual air value, and determine the calibration value according to the air standard value and the actual air value.

[0037] The standard air value refers to the value obtained by the scanning device when scanning the air under predetermined parameters, while the actual air value refers to the value obtained by the scanning device when scanning the air under the current parameters.

[0038] Since the scanning device scans both the air area and the scanning object, the air area can be used as a reference for calibrating the scanning results of the scanning object. Specifically, the deviation between the actual air value and the standard air value can be identified as the deviation between the data to be calibrated obtained from the scanning object and the standard value of that data. Furthermore, the deviation between the actual air value and the standard air value is determined as a calibration value and used to calibrate the data to be calibrated.

[0039] Step 206: Correct the data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or the second data whose acquisition time meets a preset condition with the first data.

[0040] If the data to be calibrated is the first data, since the scanning device scans both the air region and the scanning body under the current parameters, and the parameters used when scanning the air region and the scanning body are the same, the deviations in the corresponding data will also be the same. Based on this, the air region can be used as a reference object for calibrating the scanning results of the scanning body. Specifically, the deviation between the actual air value and the standard air value can be identified as the deviation between the data to be calibrated obtained by scanning the scanning body and the standard value of that data. Further, the deviation between the actual air value and the standard air value is determined as the calibration value and used to calibrate the data to be calibrated.

[0041] The above technical solution utilizes the consistency of parameters used by the scanning equipment to scan the air region and the scanned object in a single scan. It uses the air data within a single scan as a calibration reference to calibrate the data to be corrected on the scanned object; that is, it uses the actual air values ​​of the current scan to correct the data of the scanned object. This avoids the error caused by parameter differences in the scanning equipment between different scans, achieving real-time online calibration, improving calibration accuracy, and contributing to the acquisition of more accurate and reliable diagnostic images.

[0042] If the data to be corrected is the second data whose acquisition time meets the preset conditions as the first data, since the air region data of the first data is acquired online and the acquisition time meets the preset conditions as the second data, the contribution of air to the first data and the contribution to the second data are basically the same within the preset conditions. The contribution includes the projection value of air in the projection domain and the gray value of air in the image domain. Basically the same means the same or fluctuating within 10%. Therefore, the correction value obtained based on the air region data of the first data can be used as a reference object for correcting the second data. This avoids the error caused by the parameter difference of the scanning equipment between different scans on the calibration operation, realizes online correction, improves the accuracy of calibration, and helps to obtain more accurate and reliable diagnostic images.

[0043] In one possible design, the preset condition is: the acquisition time of the first data is closest to the acquisition time of the second data; or the interval between the acquisition time of the first data and the acquisition time of the second data is within a preset time range, wherein the preset time range is determined by temperature change information or humidity change information of the scanning environment, or by the usage time of the scanning device. Specifically, the contribution of air to the data is mainly affected by the temperature and humidity of the scanning environment and the duration of use of the scanning equipment. Regarding the impact of the scanning environment, generally, when the temperature or humidity of the scanning environment remains constant, the contribution of air to the data is basically consistent. The preset duration range is determined by the temperature or humidity change information of the scanning environment, including: monitoring the temperature or humidity change of the scanning environment. When the temperature or humidity change is within the preset threshold, the preset duration can be 24 hours, 12 hours, or within the continuous working time of the scanning equipment (without stopping after the scanning equipment is turned on) and the first data is the data of the area containing air that the scanning equipment first acquires. When the temperature or humidity change is outside the preset threshold, the preset duration can be the first data that is furthest from the current time and whose difference from the current temperature or humidity value is within the preset threshold range. The preset threshold for temperature can be ±2℃, and the preset threshold for humidity can be ±5%. Regarding the impact of the scanning equipment's usage time, the longer the scanning equipment is used, the greater the probability of changes in the intensity and spectrum of the X-ray tube, and the greater the difference in the contribution of air to the data. Therefore, the preset time range can be 1 hour, 2 hours, 3 hours or 5 hours before the second data acquisition, which can be determined according to the performance of the X-ray tube (heat capacity and heat dissipation capacity).

[0044] Finally, by using a calibration value that reflects the deviation between the actual air value and the standard air value, the data to be calibrated obtained by scanning the object is corrected to obtain the standard value of the data to be calibrated, which is the target data.

[0045] The above technical solution uses the air data obtained from the scan as a calibration reference to calibrate the scan results corresponding to the scanned body, which can improve the accuracy of calibration and help to obtain more accurate and reliable diagnostic images.

[0046] In one possible design, prior to step 204, the method further includes: extracting the air region data from the first data.

[0047] Specifically, the target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector is first obtained.

[0048] The fact that the ray was received directly by the detector without passing through the scanning body indicates that the scanned object was an air region, meaning it passed through air before being received by the detector. The target detection channel containing this ray is the detection channel for scanning the air region; in other words, it's the detection channel used to acquire air region data. Therefore, the data corresponding to the target detection channel in the first data can be extracted as the air region data. Since this data is unaffected by the tissue (organ type, lesion type) within the scanning body, it better reflects the impact of differences in scanning equipment parameters and scanning environment between different scans. This avoids the problem of lesion region values ​​being corrected to normal values ​​when using data from the scanning body region for calibration, which could lead to misdiagnosis (missed diagnosis or false alarm) by the doctor.

[0049] In one possible design, one way to obtain the target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector is as follows: obtain the projection curve of each detection channel in the detector, wherein the projection curve represents the relationship between the detection channel position and the projection value, wherein if the first data is image domain data, the first data is orthographically projected to obtain the projection curve of each detection channel; based on the projection curve of each detection channel, the detection channel whose deviation value from zero is within a specified deviation range is determined as the target detection channel.

[0050] If the first data is image domain data, the projection curve represents the relationship between the detection channel position and the projection value. Since the attenuation of rays is minimal when passing through the air region, the location where the projection value is close to zero is where the air region is located.

[0051] Based on this, a specified deviation range can be set as a reasonable deviation range between the projected value and zero value generated after the ray attenuates through the air region. Once the deviation between the projected value and zero value corresponding to any detection channel is within the specified deviation range, the detection channel can be determined as the target detection channel for scanning the air region.

[0052] In another possible design, one way to obtain the target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector is as follows: obtain the target image region outside the region where the scanning body is located in the first data, wherein if the first data is projection domain data, the first data is back-projected and reconstructed to obtain the image domain data corresponding to the first data; the detection channel corresponding to the target image region is obtained as the target detection channel.

[0053] If the first data is projection domain data, it can be back-projected and reconstructed to obtain its corresponding image domain data; in other words, the first data is restored to a scanned image. The target image region in the image domain data is the image region where the air is located, and the detection channel corresponding to the image region where the air is located is the target detection channel. The image region where the air is located in the image domain data can be identified using image recognition algorithms or thresholding methods. These image recognition algorithms include, but are not limited to, any one of the following algorithms: depth-first search, breadth-first search, A* search, Dijkstra's algorithm, Bellman-Ford algorithm, Floyd-Warshall algorithm, Prim algorithm, and Kruskal algorithm.

[0054] Optionally, the air region data includes multiple sets of air region sub-data, each set of air region sub-data corresponding to a detection channel layer, and a detection channel layer including multiple target detection channels. Specifically, the detector's detection channel layers are generally arranged along the Z direction, and each layer includes multiple detection channels along the X direction. The Z direction is the extension direction of the scanning aperture and also the horizontal feed direction of the scanning bed, while the X direction is perpendicular to the Z direction. The air region data acquired by the same layer of detection channels constitutes a set of air region sub-data.

[0055] Based on this, step 204 specifically includes: selecting at least one set of air region sub-data from the multiple sets of air region sub-data; obtaining the average air value of all target detection channels in the at least one set of air region sub-data, and using the average air value as the actual air value; obtaining the difference between the standard air value and the actual air value, and using the difference as the calibration value of all detection channels, wherein the difference includes grayscale value or projection value.

[0056] Specifically, one or more sets of air region sub-data can be selected from all air region sub-data, and the average air value of all target detection channels in one or more sets of air region sub-data can be calculated as the actual air value. That is, the average air value within one or more sets of air region sub-data is used as the actual air value of all air region data.

[0057] In another possible design, step 204 specifically includes: obtaining the average air value of the target detection channel in each group of air region sub-data in the multiple groups of air region sub-data, and using the average air value of each group of air region sub-data as the actual air value of all detection channels in the detection channel layer; obtaining the difference between the actual air value and the standard air value of each detection channel layer as the calibration value of all detection channels in each detection channel layer, wherein the difference includes grayscale value or projection value.

[0058] Specifically, for each set of air region sub-data, the average air value of the target detection channel for that air region sub-data can be calculated as the actual air value for that air region sub-data. Then, based on the difference between the actual air value of that air region sub-data and the air standard value, a unique calibration value for each layer of detection channel is obtained. Thus, more accurate calibration values ​​can be set for different air region sub-data, helping to improve calibration accuracy.

[0059] In one possible design, the first data is planar or tomographic data, and the second data is tomographic data. Tomographic data, also known as slice data, is obtained by scanning equipment using axial or helical scanning.

[0060] In other words, the air region of the planar radiograph data can be used as a reference standard to calibrate the tomographic data.

[0061] In one possible design, the planar radiograph data can be the corresponding planar radiograph data from the tomographic data to be calibrated in the current scan. That is, the first data is planar radiograph data, the second data is tomographic data, and the first data is data used to locate the region of interest of the scanned body before the scan that acquired the second data. In other words, it is possible to use the air regions of the tomographic data in the historical scan data prior to the current scan as a reference standard to perform overall calibration of the tomographic data in the current scan.

[0062] In another possible design, the flat film data can also be flat film data from historical scan data prior to this scan.

[0063] Alternatively, the air region of the fault data can be used as a reference standard to perform overall calibration of the fault data.

[0064] In one possible design, the air region in the tomographic data of this scan can be used as a reference standard to calibrate the tomographic data of this scan as a whole.

[0065] It should be added that the first data and the second data can be data obtained through real-time scanning or data that has undergone preliminary correction. The preliminary correction involves obtaining a correction table offline and using this table to correct the measured values ​​to standard values. The correction table includes the correction correspondence between the measured values ​​and the standard values. In other words, the scanned data can be preliminarily corrected before implementing the correction method described in any of the above technical solutions.

[0066] Example 2

[0067] Figure 3 A flowchart of a data processing method according to another embodiment of this application is shown.

[0068] like Figure 3 As shown, a data processing method according to another embodiment of this application includes:

[0069] Step 302: Determine the air zone.

[0070] Scanning includes, but is not limited to, plain CT scans, enhanced CT scans, CT angiography, CT perfusion scans, and all other scanning methods that require a combination of scanning projection and image reconstruction to obtain diagnostic or therapeutic images of the scanned object. Specific scanning methods include, but are not limited to, computed tomography (CT) and helical scanning. The scanned object includes, but is not limited to, any object requiring diagnosis or simulation, such as the human body, animal body, plant body, or phantom. Different parts of the scanned object and areas of air have different densities, resulting in varying absorption capacities for radiation, leading to different attenuation results after radiation passes through. The projection values ​​of a CT image reflect the attenuation of radiation emitted by the CT equipment after passing through the scanned object. Optionally, the radiation emitted by the CT equipment includes, but is not limited to, X-rays.

[0071] Combination Figure 1 As shown in the cross-sectional view of the scanning channel, when the scanning body is located in the scanning channel, it cannot completely fill the channel; air is also present within the scanning channel, in addition to the scanning body. Therefore, the data obtained from the scan, the data outside the area where the scanning body is located, represents the data of the air region.

[0072] Step 304: Determine the calibration value based on the air standard projection value and the projection value of the air area.

[0073] The standard air projection value refers to the projection value obtained by a CT scanner scanning air under predetermined parameters, typically 0 HU. Since the air region and the scanned object are scanned by the same CT scanner under the same current parameters, the deviation between the air region's projection value and the standard air projection value represents the deviation between the projection value of the scanned object in the CT image and the projection value that the scanned object should have obtained when scanned by the CT scanner under predetermined parameters. Therefore, the calibration value is used to reflect the relative magnitude of the projection value of the CT image and its expected standard projection value.

[0074] Specifically, the difference between the standard air projection value and the projection value of the air area can be determined as the calibration value.

[0075] In one possible design, the predetermined parameters can be the factory parameters of the CT equipment.

[0076] In another possible design, the predetermined parameters can be selected as the actual parameters of the CT device when performing the first scan or any other specified scan.

[0077] Step 306: Based on the calibration value, correct all projection data of this scan or subsequent scans to obtain corrected projection values, which are used to construct the diagnostic image of the scanned body.

[0078] Since the calibration value reflects the relative size of the projection value of the CT image to its standard projection value, for all projection data of the current or subsequent scans, the calibration value can be subtracted from all projection data to obtain a more accurate and reliable corrected projection value, which can be used to construct the diagnostic image of the scanned body.

[0079] For the calibration of the current scan data (i.e., the first data), since the CT scanner scans both the air region and the scanned object in a single scan, meaning both are scanned by the same CT scanner under the same parameter conditions, the air region can be used as a reference object for calibrating the scanned object's results. Therefore, selecting a calibration reference object under the same parameter conditions for calibrating the scanned object's results helps improve the accuracy of the calibration.

[0080] For the calibration of subsequent scan data (i.e., the second data), although the scanning parameters of this scan and subsequent scans may be different, the differences in factors such as the scanning environment are very small. Therefore, the calibration value obtained in this scan can be used to calibrate subsequent scans, realizing online calibration.

[0081] In one possible design, for the CT image (one detection channel layer) corresponding to a single scanning layer in the scan, a first mean value of the projection values ​​of all pixels (one pixel corresponds to one detection channel) in the air region of the CT image is obtained; the difference between the first mean value and the standard projection value of the air region is determined as the calibration value of the single scanning layer.

[0082] Optionally, when selecting CT images obtained from scanning the scanned body, such as... Figure 6 For the 90-degree flat image shown, the difference between the standard projection value of the air and the projection value of each pixel in the air region of the 90-degree flat image is obtained, and the average of these differences is used as the calibration value for this scan.

[0083] Therefore, the calibration value determined by the air region within a single scan layer can be used as the unified calibration value for all scan layers. This calculation is quick and convenient, improving the efficiency of acquiring diagnostic images.

[0084] In another possible design, for all scan layers (multiple detection channel layers) in the scan, a second mean of the projection values ​​of all pixels in the air region of all scan layers is obtained; the difference between the second mean and the air standard projection value is determined as the calibration value of all scan layers.

[0085] Therefore, a uniform calibration value can be set for all scanning layers, so that the obtained calibration value encompasses the accuracy of each scanning layer, reflects the average accuracy level of all scanning layers, and improves the reliability of the final diagnostic image.

[0086] In other possible designs, the grayscale values ​​of pixels in the air region of the CT image can be obtained directly without projection processing. In the image domain, each pixel of the CT image to be corrected is calibrated based on the grayscale values.

[0087] Example 3

[0088] Figure 4 A flowchart of a data processing method according to another embodiment of this application is shown.

[0089] like Figure 4 As shown, a data processing method according to another embodiment of this application includes:

[0090] Step 402: Based on the offline calibration data, perform offline calibration on all projection data of this scan.

[0091] Before implementing the online calibration described in any embodiment of this application, all projection data obtained from this scan can first be calibrated offline, thereby combining offline calibration with online calibration to correct all projection data, further improving the accuracy of the projection data used to reconstruct diagnostic images, and helping to improve the reliability of diagnostic images.

[0092] The offline calibration data can be selected as the closest scan result before this scan.

[0093] Step 404: After offline calibration, determine the air region in a single scan layer.

[0094] Step 406: Determine the calibration value based on the air standard projection value and the projection value of the air area, and save the calibration value as a calibration table file.

[0095] Step 408: Based on the calibration table file, perform a secondary calibration process on all projection data after offline calibration.

[0096] In one possible design, the calibration table file records the calibration value corresponding to the current scan, which is read during CT equipment maintenance to facilitate understanding and evaluation of the CT equipment's usage, and / or to provide the calibration value corresponding to the current scan when a valid air area or valid calibration value cannot be obtained in any subsequent scan.

[0097] Step 410: Based on the results of the secondary calibration process, the reconstructed diagnostic and treatment images are obtained through filtered back projection image reconstruction.

[0098] This technical solution combines offline and online calibration to calibrate all the projection data obtained from the scan, which can obtain more accurate projection data, thereby facilitating the acquisition of more accurate and reliable diagnostic images and helping to improve the safety of diagnosis and treatment.

[0099] Example 4

[0100] Figure 5 A flowchart of a data processing method according to another embodiment of this application is shown.

[0101] like Figure 5 As shown, a data processing method according to another embodiment of this application includes:

[0102] Step 502: Based on the offline calibration data, perform offline calibration on all projection data of this scan.

[0103] Before implementing the online calibration described in any embodiment of this application, all projection data obtained from this scan can first be calibrated offline, thereby combining offline calibration with online calibration to correct all projection data, further improving the accuracy of the projection data used to reconstruct diagnostic images, and helping to improve the reliability of diagnostic images.

[0104] Step 504: After offline calibration, determine whether the current scan includes a 90-degree flat section scan.

[0105] 90 degrees refers to the angle of the X-ray tube. Generally, the X-ray tube is 0 degrees or 180 degrees in the vertical direction and 90 degrees or 270 degrees in the horizontal direction.

[0106] A 90-degree plain film image refers to a CT image obtained when the X-ray tube is at a 90-degree position. Figure 6 This is a cross-sectional view of the initial projection of the scanned human body in a 90-degree planar image. In, for example... Figure 6 In the 90-degree planar image shown, there are valid air regions on both the left and right sides of the human body. Therefore, the 90-degree planar image likely contains valid air regions.

[0107] In one possible design, the non-90-degree flat image in the projection data is calibrated online using the calibration value corresponding to the air region of the 90-degree flat image.

[0108] In another possible design, the non-90-degree flat image in the projection data also needs to have an effective air area so that its own air area can be used as a calibration reference to perform online calibration of the projection value of the scanned body in this scan.

[0109] In any of the above embodiments, if the air region is not detected in the CT image obtained by scanning the scanned body or the area of ​​the air region is lower than a predetermined area threshold, then a corresponding calibration value cannot be generated for this scan. The predetermined area threshold refers to the minimum area of ​​the air region in the CT image that can be used as a valid calibration reference object.

[0110] To address this, historical calibration values ​​generated from the previous scan can be obtained to construct a diagnostic image of the scanned body based on these values. Since the previous scan is most similar to the current scan, the parameters of the CT equipment during the previous scan are also most similar to those during the current scan; consequently, the calibration values ​​required for both scans are also most similar. Therefore, historical calibration values ​​generated from the previous scan can be used to ensure reliable calibration values ​​are obtained even if no air regions are detected in the current scan.

[0111] Step 506: If included, search the areas on both sides of the 90-degree flat film to determine the range of the air area.

[0112] Step 508: Calculate the mean of the projected values ​​of the air region within the range of the air region.

[0113] Step 510: Determine the difference between the mean value and the air standard projection value as the calibration value, and save the calibration value as a calibration table file.

[0114] Figure 7 It shows Figure 6 The variation of the projection values ​​corresponding to the 90-degree planar image shown is as follows: Figure 7 On the coordinate system, the left and right sides of the lines correspond to the air regions to the left and right of the human body, and the curves correspond to the human body. Of course, in actual scanning, the complexity of the curves corresponding to the human body is much greater than that of the human body. Figure 7 As shown. The straight lines on the left and right indicate that the projection values ​​are the same everywhere in the air area. When the standard projection value of air is 0, the projection values ​​corresponding to the left and right straight lines are slightly lower than 0, and the difference between them and 0 is the calibration value.

[0115] In one possible design, the specific method for determining the extent of the air region is as follows: In the CT image, determine the target side (the location where the air region exists) located on the scanning body; on the target side, determine the target position, and using the target position as the starting point, along the arrangement direction of the detection channel layer of the CT image and the arrangement direction of multiple detection channels within the detection channel layer, respectively, obtain the first target pixel whose projection value is greater than or equal to a predetermined projection value threshold; based on the target position and the position of the target pixel, determine a rectangular region as the air region corresponding to the target side. The arrangement direction of the detection channel layer can be... Figure 6 The vertical direction, the arrangement direction of multiple detection channels within the detection channel layer can be... Figure 6 The left and right directions.

[0116] Specifically, the target side of the scanning body in the CT image includes at least one of the upper, lower, left, and right sides of the scanning body, for example, in Figure 6 In this model, the target sides of the human body are the left and right sides. The more target sides there are, the more air area is obtained, resulting in a larger range of base data used when calculating the mean of the projection values. The resulting mean is more representative and reliable, thus effectively improving the accuracy of the further obtained calibration values ​​and increasing the reliability of the correction results.

[0117] The predetermined projection threshold refers to the minimum projection value that the scanned object should have during scanning. The projection value of the air region is much lower than the predetermined projection threshold. Therefore, when searching from the target position on the target side of the CT image along the arrangement direction of the detection channel layer and the arrangement direction of multiple detection channels within the detection channel layer, once a pixel with a projection value greater than or equal to the predetermined projection threshold is found, it can be determined as a target area unit on the scanned object. The distance from the target position on the target side to this target area unit is the width of the air region on that target side of the scanned object.

[0118] If a single target location is selected on any of the target sides, a rectangular area is obtained accordingly.

[0119] If multiple target locations are selected on any one of the target sides, then based on the different distances from each target location to the scanning body, multiple more finely divided rectangular regions of varying lengths can be obtained. In other words, for any one of the target sides, when there are multiple target locations, the air region on that target side is composed of multiple rectangular regions corresponding to each target location. The more rectangular regions there are, the finer the division, the more accurate the area of ​​the determined air region, and the more accurate the average of the projection values ​​calculated based on the air regions, thus obtaining more accurate calibration values ​​and increasing the reliability of the calibration results.

[0120] Step 512: Based on the calibration table file, perform a secondary calibration process on all projection data after offline calibration.

[0121] Step 514: Based on the results of the secondary calibration process, the reconstructed diagnostic and treatment images are obtained through filtered back projection image reconstruction.

[0122] The above technical solutions combine offline and online calibration to calibrate the projection data. They can also determine the range of the air area by dividing the area into rectangular regions. By improving the accuracy of the air area division, the accuracy of the calibration value calculation is effectively improved, which helps to increase the reliability of the calibration results.

[0123] Example 5

[0124] Figure 8 A flowchart of a data processing method according to yet another embodiment of this application is shown.

[0125] like Figure 8 As shown, a data processing method according to another embodiment of this application includes:

[0126] Step 802: Based on the offline calibration data, perform offline calibration on all projection data of this scan.

[0127] Step 804: Filter and backproject the entire projection data after offline calibration to reconstruct the initial image.

[0128] Step 806: Identify air regions in the initial image using an image recognition algorithm.

[0129] Step 808: Based on the air regions in the initial image, determine the air regions of a single scan layer.

[0130] Specifically, air regions in the initial image can be identified directly using an image recognition algorithm, or the scanning object in the initial image can be identified using an image recognition algorithm, and the area outside the scanning object is then defined as an air region. Next, based on the correspondence between the initial image and the CT image of the single scanning layer, the air region of the single scanning layer is determined.

[0131] The image recognition algorithm includes, but is not limited to, any one of the following algorithms: depth-first search, breadth-first search, A* search algorithm, Dijkstra, Bellman-Ford, Floyd-Warshall, Prim, and Kruskal. Of course, it can also be any other algorithm that can identify air regions, and there are no restrictions here.

[0132] Using image recognition algorithms can obtain more accurate recognition content, that is, obtain a more accurate range of air regions, and improve the accuracy of air region division.

[0133] Step 810: Obtain the calibration value of the air region in the CT image of the single scan layer, and save the calibration value as a calibration table file.

[0134] Step 812: Based on the calibration table file, perform a secondary calibration process on all projection data after offline calibration.

[0135] Step 814: Based on the results of the secondary calibration process, the reconstructed diagnostic and treatment images are obtained through filtered back projection image reconstruction.

[0136] The above technical solutions combine offline and online calibration to calibrate the projection data, while also using image recognition algorithms to accurately delineate the range of air regions, improving the accuracy of air region delineation and effectively enhancing the accuracy of calibration value calculation, thus increasing the reliability of the calibration results.

[0137] Figure 9 A block diagram of a data processing apparatus according to an embodiment of this application is shown.

[0138] like Figure 9 As shown, a data processing apparatus 900 according to an embodiment of this application includes: a first data acquisition unit 902, configured to acquire first data including air region data, wherein the first data is image domain data or projection domain data; a calibration value acquisition unit 904, configured to acquire actual air values ​​based on the air region data in the first data, and determine a calibration value based on an air standard value and the actual air values; and a correction processing unit 906, configured to correct the data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or second data whose acquisition time with the first data meets a preset condition.

[0139] In one possible design, the data processing device 900 further includes: an air region data acquisition unit, configured to extract the air region data from the first data before the calibration value acquisition unit 904 acquires the actual air value, wherein the target detection channel in the first data is acquired where the ray does not pass through the scanning body and is directly received by the detector; and the data corresponding to the target detection channel in the first data is extracted as the air region data.

[0140] In one possible design, the calibration value acquisition unit 904 is used to: acquire the projection curve of each detection channel in the detector, the projection curve representing the relationship between the detection channel position and the projection value, wherein, if the first data is image domain data, the first data is orthographically projected to acquire the projection curve of each detection channel; based on the projection curve of each detection channel, the detection channel whose deviation value between the projection value and the zero value is within a specified deviation range is determined as the target detection channel.

[0141] In one possible design, the calibration value acquisition unit 904 is used to: acquire a target image region outside the region where the scanning body is located in the first data, wherein if the first data is projection domain data, the first data is back-projected and reconstructed to acquire the image domain data corresponding to the first data; and acquire the detection channel corresponding to the target image region as the target detection channel.

[0142] In one possible design, the air region data includes multiple sets of air region sub-data, each set of air region sub-data corresponding to a detection channel layer, and a detection channel layer including multiple target detection channels. The calibration value acquisition unit 904 is used to: select at least one set of air region sub-data from the multiple sets of air region sub-data; acquire the air average value of all target detection channels in the at least one set of air region sub-data, and use the air average value as the actual air value; acquire the difference between the air standard value and the actual air value, and use the difference as the calibration value of all detection channels, wherein the difference includes grayscale value or projection value.

[0143] In one possible design, the air region data includes multiple sets of air region sub-data, each set of air region sub-data corresponding to a detection channel layer, and a detection channel layer including multiple target detection channels. The calibration value acquisition unit 904 is used to: acquire the average air value of the target detection channels of each set of air region sub-data in the multiple sets of air region sub-data, and use the average air value of each set of air region sub-data as the actual air value of all detection channels in the detection channel layer; acquire the difference between the actual air value and the air standard value of each detection channel layer, and use it as the calibration value of all detection channels in each detection channel layer, wherein the difference includes grayscale value or projection value.

[0144] In one possible design, the first data is planar data or tomographic data, and the second data is tomographic data.

[0145] In one possible design, the first data is planar data, the second data is tomographic data, and the first data is data used to locate the region of interest of the scanned body before the scan to acquire the second data is performed.

[0146] In one possible design, the preset condition is: the acquisition time of the first data is closest to the acquisition time of the second data; or the interval between the acquisition time of the first data and the acquisition time of the second data is within a preset time range, wherein the preset time range is determined by temperature change information or humidity change information of the scanning environment, or by the usage time of the scanning device.

[0147] In one possible design, the first data and the second data are data that have undergone preliminary correction. The preliminary correction is a process of obtaining a correction table offline and correcting the measured values ​​to standard values ​​using the correction table. The correction table includes the correction correspondence between the measured values ​​and the standard values.

[0148] The data processing device 900 uses the solution described in any one of the above embodiments, and therefore has all the above-mentioned technical effects, which will not be repeated here.

[0149] Additionally, one embodiment of this application provides a CT device, which includes: an internal bus, and a memory, a processor, and an external interface connected via the internal bus, wherein the external interface is used to connect to the detectors of the CT system, the detectors including multiple detector chambers and corresponding processing circuits; the memory is used to store computer-executable instructions corresponding to CT scanning logic; the processor is used to read the computer-executable instructions on the memory and execute the method described in any of the above embodiments based on the computer-executable instructions.

[0150] One embodiment of this application also provides a CT equipment control terminal, which includes: at least one memory; and a processor communicatively connected to the at least one memory; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to execute the scheme described in any of the above embodiments. Therefore, this CT equipment control terminal has the same technical effects as any of the above embodiments, and will not be repeated here.

[0151] The CT equipment control terminal of this application embodiment can exist in various forms, including but not limited to:

[0152] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0153] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0154] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes audio and video players (such as iPods), handheld game consoles, e-book readers, as well as smart toys and portable car navigation devices.

[0155] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0156] (5) Other electronic devices with data interaction functions.

[0157] In addition, this application embodiment provides a storage medium storing computer-executable instructions for performing the following steps: acquiring first data including air region data, wherein the first data is image domain data or projection domain data; acquiring actual air values ​​based on the air region data in the first data, and determining a calibration value based on the air standard value and the actual air value; and correcting the data to be corrected based on the calibration value to obtain target data, wherein the data to be corrected is the first data, or second data whose acquisition time with the first data meets a preset condition.

[0158] It should be noted that the functions or steps that the storage medium or device can achieve are described in the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0159] The technical solution of this application has been described in detail above with reference to the accompanying drawings. The technical solution of this application uses the air data obtained by scanning as a calibration reference object to calibrate the scanning results corresponding to the scanning body, which can improve the accuracy of calibration and help to obtain more accurate and reliable diagnostic and treatment images.

[0160] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0161] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0162] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0163] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0164] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0165] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0166] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A data processing method, characterized in that, include: Acquire first data including air region data, wherein the first data is image domain data or projection domain data; Based on the air region data in the first data, the actual air value is obtained, and the calibration value is determined according to the air standard value and the actual air value; The data to be corrected is corrected based on the calibration value to obtain the target data. The data to be corrected is second data whose acquisition time satisfies a preset condition compared to the first data. The preset condition is: The time interval between the acquisition time of the first data and the acquisition time of the second data is within a preset time range, wherein the preset time range is determined by the usage time of the scanning device.

2. The data processing method according to claim 1, characterized in that, Before obtaining the actual air quality value based on the air region data in the first data, the method further includes: extracting the air region data from the first data. The step of extracting the air region data from the first data includes, The target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector; Extract the data corresponding to the target detection channel from the first data, and use it as the air area data.

3. The data processing method according to claim 2, characterized in that, The acquisition of the target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector includes: The projection curve of each detection channel in the detector is obtained. The projection curve represents the relationship between the position of the detection channel and the projection value. If the first data is image domain data, the first data is orthographically projected to obtain the projection curve of each detection channel. Based on the projection curve of each detection channel, the detection channel whose deviation value from the zero value is within a specified deviation range is determined as the target detection channel.

4. The data processing method according to claim 2, characterized in that, The acquisition of the target detection channel in the first data where the ray does not pass through the scanning body but is directly received by the detector includes: Obtain the target image region outside the area where the scanning body is located in the first data, wherein if the first data is projection domain data, the first data is back-projected and reconstructed to obtain the image domain data corresponding to the first data; The detection channel corresponding to the target image region is obtained as the target detection channel.

5. The data processing method according to claim 2, characterized in that, The air region data includes multiple sets of air region sub-data, each set of air region sub-data corresponding to a detection channel layer, and a detection channel layer including multiple target detection channels. Obtaining the actual air value based on the air region data in the first data includes: Select at least one set of air region sub-data from the plurality of sets of air region sub-data; Obtain the average air value of all target detection channels in the at least one set of air region sub-data, and use the average air value as the actual air value; The process of determining the calibration value based on the air standard value and the actual air value includes: The difference between the standard air value and the actual air value is obtained, and the difference is used as the calibration value for all target detection channels. The difference includes grayscale value or projection value.

6. The data processing method according to claim 2, characterized in that, The air region data includes multiple sets of air region sub-data, each set of air region sub-data corresponding to a detection channel layer, and a detection channel layer including multiple target detection channels. Obtaining the actual air value based on the air region data in the first data includes: The average air value of the target detection channel in each group of air region sub-data is obtained, and the average air value of each group of air region sub-data is used as the actual air value of all detection channels in the corresponding detection channel layer. The process of determining the calibration value based on the air standard value and the actual air value includes: The difference between the actual air value and the standard air value of each detection channel layer is obtained and used as the calibration value for all detection channels within each detection channel layer. The difference includes grayscale value or projection value.

7. The data processing method according to claim 1, characterized in that, The first data is planar radiograph data or fault data, and the second data is fault data.

8. The data processing method according to claim 7, characterized in that, The first data is planar radiograph data, the second data is tomographic data, and the first data is data used to locate the region of interest of the scanned body before the scan to acquire the second data is performed.

9. The data processing method according to claim 7, characterized in that, Under the preset conditions, the contribution of air to the first data and the contribution to the second data are basically the same.

10. The data processing method according to any one of claims 1 to 9, characterized in that, The first data and the second data are data that have undergone preliminary correction. The preliminary correction is a process of obtaining a correction table offline and correcting the measured values ​​to standard values ​​using the correction table. The correction table includes the correction correspondence between the measured values ​​and the standard values.

11. A data processing apparatus, characterized in that, include: The first data acquisition unit is used to acquire first data including air area data, wherein the first data is image domain data or projection domain data. The calibration value acquisition unit is used to acquire the actual air value based on the air area data in the first data, and to determine the calibration value according to the air standard value and the actual air value; A calibration processing unit is used to calibrate the data to be calibrated based on the calibration value to obtain target data. The data to be calibrated is a second data whose acquisition time with the first data meets a preset condition. The preset condition is that the time interval between the acquisition time of the first data and the acquisition time of the second data is within a preset time range. The preset time range is determined by the usage time of the scanning device.

12. A CT scanner, characterized in that, This includes: an internal bus, and memory, processor, and external interfaces connected via the internal bus, wherein, The external interface is used to connect to the detector of the CT system, and the detector includes multiple detector chambers and corresponding processing circuits. The memory is used to store computer-executable instructions corresponding to the CT scan logic; The processor is configured to read the computer-executable instructions on the memory and execute the method of any one of claims 1 to 10 based on the computer-executable instructions.

13. A storage medium, characterized in that, The device stores computer-executable instructions for performing the method flow as described in any one of claims 1 to 10.

Images