Scanning method and device for CT (Computed Tomography) equipment and CT equipment

Abstract

The invention relates to the technical field of CT equipment, and discloses a scanning method for CT equipment, which comprises the following steps: acquiring electrocardiogram data of a patient; detecting and analyzing the ST segment of the electrocardio data to obtain a judgment result of the severity of myocardial ischemia of the patient; and executing a relative scanning operation according to the obtained judgment result. According to the method, the myocardial ischemia state can be recognized in real time, dynamic intervention can be conducted, real-time monitoring and intelligent processing of the myocardial ischemia phenomenon are achieved by accurately analyzing the characteristic electrocardiosignals of the patient, and the patient can be prevented from being seriously harmed due to aggravation of myocardial ischemia in the scanning process. The invention further discloses a scanning device for the CT equipment and the CT equipment.

Description

Technical Field

[0001] The present application relates to the technical field of CT equipment, for example, to a scanning method and device for CT equipment, and CT equipment. Background Art

[0002] In modern medical diagnosis, CT (Computed Tomography) perfusion cardiac scans are widely used to assess a patient's coronary artery and myocardial perfusion function. By injecting contrast agents and acquiring continuous cardiac images, comprehensive anatomical and functional information can be obtained. However, when patients undergo CT cardiac perfusion scans, various factors (such as a sudden increase in cardiac load caused by contrast agents and cardiovascular stress caused by patient anxiety) may trigger or aggravate myocardial ischemia. Without real-time, effective monitoring and intervention methods, patients may face safety risks during the scan.

[0003] Related technologies disclose a CT scan control device and system that uses ECG signals to determine whether a patient is in a preset ECG state, thereby triggering a cardiac CT scan to determine if the patient's heart rhythm is normal, reducing human intervention. The key is to compare the real-time ECG signals with a preset reference signal (such as a standard ECG signal from a healthy individual or a typical arrhythmia signal) through a signal comparison method to determine whether the patient is suitable for further scanning.

[0004] During the implementation of the embodiments of the present disclosure, it was found that at least the following problems exist in the related art:

[0005] The relevant technology is limited to monitoring the overall ECG status (such as abnormal heart rhythm or heart rate), and cannot conduct in-depth analysis of specific characteristics of myocardial ischemia (such as ST segment changes), nor does it provide real-time linkage management of dynamic changes that occur in patients during the scanning process.

[0006] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0007] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0008] The embodiments of the present disclosure provide a scanning method and apparatus for a CT device, and a CT device, which can identify myocardial ischemia in real time and perform dynamic intervention.

[0009] In some embodiments, the scanning method for CT equipment includes: acquiring the patient's electrocardiogram data; detecting and analyzing the ST segment of the electrocardiogram data to obtain a judgment result on the severity of the patient's myocardial ischemia; and performing a relative scanning operation based on the obtained judgment result.

[0010] Optionally, obtaining the patient's ECG data includes: transmitting the collected first-lead ECG data and second-lead ECG data to the console; reconstructing the third-lead ECG data based on the received first-lead ECG data and second-lead ECG data; and selecting target lead ECG data to make a myocardial ischemia judgment.

[0011] Optionally, obtaining the patient's ECG data includes: obtaining the patient's first-lead ECG data and second-lead ECG data; controlling the underlying ECG data receiving board to calculate and obtain the third-lead ECG data; and transmitting part of the lead ECG data to the myocardial ischemia automatic judgment module of the console according to analysis requirements.

[0012] Optionally, the ST segment of the electrocardiogram data is detected and analyzed to obtain a judgment result on the severity of the patient's myocardial ischemia, including: extracting characteristic data of the ST segment; wherein the characteristic data includes offset and / or duration; according to preset thresholds and grading standards, using a machine learning model or a lookup table method to evaluate and grade the characteristic data to obtain a judgment result on the severity of the patient's myocardial ischemia.

[0013] Optionally, based on the obtained judgment result, a relative scanning operation is performed, including: when the judgment result is that there is no offset or abnormality, continuing the scan; when the judgment result is that the offset is n1mV, or the duration is m1 minute, issuing a prompt message and continuing the scan; the first threshold ≤ n1 ≤ the third threshold, m1 ≤ the fifth threshold; when the judgment result is that the offset is n3mV, or the duration is m3 minutes, terminating the scan; n3>the third threshold, m3>the fifth threshold.

[0014] Optionally, when the judgment result is an offset of n1mV, or a duration of m1 minutes, a prompt message is issued and the scan continues, including: when the judgment result is an offset of n2mV, or a duration of m2 minutes, scanning is performed according to the user's manual confirmation information; the second threshold ≤n2≤the third threshold, the fourth threshold ≤m2≤the fifth threshold.

[0015] Optionally, when the judgment result is an offset of n2mV, or a duration of m2 minutes, scanning is performed according to the user's manual confirmation information, including: continuing the scanning if confirmation information for continuing the scanning is received within the set time; terminating the scanning if no confirmation information for continuing the scanning is received within the set time.

[0016] Optionally, the scanning method for CT equipment further includes: recording the patient's electrocardiogram data and judgment results in real time; and generating an analysis report based on the electrocardiogram data and judgment results.

[0017] In some embodiments, the scanning device for CT equipment includes: an ECG data acquisition module, configured to obtain the patient's ECG data; an automatic myocardial ischemia judgment module, configured to detect and analyze the ST segment of the ECG data to obtain a judgment result on the severity of the patient's myocardial ischemia; and a scanning linkage control module, configured to perform relative scanning operations based on the obtained judgment result.

[0018] In some embodiments, the CT device includes: a CT device body; and the scanning device for the CT device as described above, installed on the CT device body.

[0019] The scanning method and apparatus for CT equipment and the CT equipment provided in the embodiments of the present disclosure can achieve the following technical effects:

[0020] In the disclosed embodiments, the patient's ECG data is acquired in real time, and the ST segment in the ECG data is accurately detected and deeply analyzed. By carefully extracting and quantitatively analyzing the ST segment features, such as monitoring the ST segment offset and duration, the severity of the patient's myocardial ischemia can be accurately determined, and the ischemic state can be finely divided into different levels such as mild, moderate, and severe. Based on the determined severity, a relative scanning operation is then performed. In this way, by accurately analyzing the patient's characteristic ECG signals, real-time monitoring and intelligent processing of myocardial ischemia can be achieved, preventing the patient from suffering serious harm due to worsening myocardial ischemia during the scanning process.

[0021] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] One or more embodiments are exemplarily described by corresponding drawings. These exemplary descriptions and drawings do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation. In addition,

[0023] Figure 1 Schematic diagram of an implementation environment of a scanning method for a CT device provided in an embodiment of the present disclosure;

[0024] Figure 2 is a schematic diagram of a scanning method for a CT device provided in an embodiment of the present disclosure;

[0025] Figure 3 is a schematic diagram of another scanning method for a CT device provided by an embodiment of the present disclosure;

[0026] Figure 4 is a schematic diagram of a scanning device for a CT device provided by an embodiment of the present disclosure;

[0027] Figure 5 It is a schematic diagram of a CT device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0029] In the description and claims of the embodiments of the present disclosure, as well as in the accompanying drawings, the terms "first," "second," and the like are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate to describe the embodiments of the present disclosure herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0030] Unless otherwise stated, the term "plurality" means two or more.

[0031] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0032] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0033] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0034] Currently, although some CT devices on the market have built-in ECG synchronization functions, they mainly focus on the heart rhythm status to trigger the optimal scanning time, reduce artifacts and improve image quality, and do not deeply analyze the key features in the ECG signal that indicate myocardial ischemia (such as ST segment changes).

[0035] Existing technologies are deficient in real-time monitoring of myocardial ischemia and in linking CT scanning processes. Although computer vision algorithms can analyze myocardial perfusion or identify signs of myocardial ischemia through post-processing of completed CT images, their reliance on post-scan processing results results in poor real-time performance and an inability to provide dynamic responses during the scanning process. Although traditional 12-lead electrocardiograms have advantages in comprehensive monitoring and accuracy, their operation is complex and their hardware deployment is time-consuming, making it difficult to meet the fast and real-time requirements of emergency CT scenarios. At the same time, the 12-lead system and CT equipment operate independently, lacking the ability for joint analysis and dynamic process intervention.

[0036] The current ECG monitoring in the CT scanning process mainly uses three-lead ECG signals to identify whether the patient is in a normal heart rhythm state to trigger the scanning operation, but the monitoring range is limited to the overall ECG state. It lacks in-depth analysis and real-time graded response capabilities for characteristic signals of myocardial ischemia (such as ST segment changes).

[0037] Figure 1 FIG. 1 is a schematic diagram of an implementation environment of a scanning method for a CT device according to an embodiment of the present disclosure. Figure 1 As shown, the implementation environment may include a CT device 100 , which includes a built-in cable 101 , a screen 102 , an alarm device 103 , and a processor 104 .

[0038] Built-in cable 101 acquires the patient's ECG signals from leads I, II, and III in real time. These signals are typically in a 16-bit format with a 500Hz sampling frequency. Processor 104 detects and analyzes these signals. Screen 102 and alarm device 103 can provide prompts and alarms, respectively, based on the analysis results obtained by processor 104.

[0039] Combine Figure 2 As shown, the embodiment of the present disclosure provides a scanning method for a CT device, comprising:

[0040] S201: The processor obtains the patient's electrocardiogram data.

[0041] S202: The processor detects and analyzes the ST segment of the electrocardiogram data to obtain a determination result on the severity of the patient's myocardial ischemia.

[0042] S203: The processor performs a relative scanning operation according to the obtained judgment result.

[0043] The scanning method for CT equipment provided in the embodiments of the present disclosure acquires the patient's electrocardiogram (ECG) data in real time, accurately detects and deeply analyzes the ST segment in the ECG data, and accurately determines the severity of the patient's myocardial ischemia through detailed extraction and quantitative analysis of ST segment features, such as monitoring ST segment offset and duration. The severity of the ischemic condition can be categorized into mild, moderate, and severe levels. Relative scanning operations are then performed based on the determined severity.

[0044] This system, through precise analysis of the patient's characteristic ECG signals, enables real-time monitoring and intelligent processing of myocardial ischemia, preventing patients from suffering serious harm due to worsening myocardial ischemia during scanning. First, real-time monitoring of myocardial ischemia and dynamic adjustment of the scanning process based on this information effectively prevents patients from being endangered by undetected myocardial ischemia during scanning. This is particularly important for high-risk patients and emergency patients, significantly reducing the risk of sudden cardiac events and safeguarding their lives. Second, through in-depth analysis of ECG data, the severity of myocardial ischemia can be accurately determined, providing physicians with more detailed and timely information on the patient's cardiac function, assisting them in making more accurate diagnoses and reducing misdiagnoses and missed diagnoses due to insufficient information. Third, it improves the quality of scan data acquired by CT equipment, increases scan success rates, avoids repeated scans, and reduces radiation dose to patients. Fourth, it implements automated scanning processes and intelligent control, eliminating the need for medical staff to closely monitor ECG status throughout the scan to determine scanning procedures, saving manpower. The system also responds quickly, adjusting scans based on myocardial ischemia determinations in a short period of time, optimizing the scanning process and improving the efficiency of CT equipment.

[0045] Optionally, obtaining the patient's ECG data includes: transmitting the collected first-lead ECG data and second-lead ECG data to the console; reconstructing the third-lead ECG data based on the received first-lead ECG data and second-lead ECG data; and selecting target lead ECG data to make a myocardial ischemia judgment.

[0046] In the embodiment of the present disclosure, the built-in ECG monitoring system of the CT device is used to collect the patient's first-lead and second-lead ECG data. The lead data is obtained through dedicated electrodes and signal acquisition modules, and can reflect the electrical activity of the patient's heart in real time. The collected first-lead and second-lead ECG data are transmitted to the console, and the console can process and analyze the ECG data in real time. In the console, the received first-lead and second-lead ECG data are processed by an algorithm to reconstruct the third-lead ECG data. The target lead ECG data is selected from the reconstructed three-lead ECG data for use in determining myocardial ischemia. The selection of the target lead is usually based on its sensitivity to the characteristics of myocardial ischemia (such as ST segment changes) to ensure the accuracy and reliability of the judgment.

[0047] Optionally, obtaining the patient's ECG data includes: obtaining the patient's first-lead ECG data and second-lead ECG data; controlling the underlying ECG data receiving board to calculate and obtain the third-lead ECG data; and transmitting part of the lead ECG data to the myocardial ischemia automatic judgment module of the console according to analysis requirements.

[0048] In the embodiment of the present disclosure, the collected first-lead and second-lead ECG data are transmitted to the underlying ECG data receiving board. The board has powerful signal processing capabilities and can obtain the third-lead ECG data based on the existing two-lead data through specific algorithms and mathematical models. This utilizes the correlation and physiological principles between the ECG leads, thereby expanding the dimension of the ECG data without increasing the cost of additional hardware. According to the analysis requirements of the automatic judgment module for myocardial ischemia, some lead ECG data (such as single-lead or three-lead data) are selected from the underlying ECG data receiving board and transmitted to the module. The automatic judgment module for myocardial ischemia will further analyze and process these data to determine whether the patient has myocardial ischemia and its severity.

[0049] The collected ECG data is preprocessed, including filtering and noise reduction, baseline drift correction, and signal optimization. Filtering and noise reduction uses digital filtering algorithms to remove high-frequency noise and low-frequency interference from the ECG data, improving the signal-to-noise ratio. Baseline drift correction removes baseline drift components from the ECG, making the ECG waveform more stable. Signal optimization further enhances the ECG waveform's characteristics, providing high-quality data for subsequent analysis.

[0050] Optionally, the ST segment of the electrocardiogram data is detected and analyzed to obtain a judgment result on the severity of the patient's myocardial ischemia, including: extracting characteristic data of the ST segment; wherein the characteristic data includes offset and / or duration; according to preset thresholds and grading standards, using a machine learning model or a lookup table method to evaluate and grade the characteristic data to obtain a judgment result on the severity of the patient's myocardial ischemia.

[0051] In an embodiment of the present disclosure, first, characteristic data of the ST segment are extracted from the preprocessed ECG data. These characteristic data include the ST segment offset (i.e., the degree of elevation or depression of the ST segment relative to the baseline) and / or duration (i.e., the duration of the abnormal ST segment state). These characteristic data can reflect the electrophysiological changes of myocardial ischemia and are key indicators for judging the severity of myocardial ischemia. Then, according to the preset threshold and classification criteria, the extracted characteristic data are input into a pre-trained machine learning model for evaluation and classification. By learning a large amount of historical ECG data, the machine learning model can identify the complex relationship between ST segment characteristic data and the severity of myocardial ischemia, and accurately classify the current patient's myocardial ischemia state based on this, such as mild ischemia, moderate ischemia, and severe ischemia. Finally, the machine learning model outputs a judgment result on the severity of the patient's myocardial ischemia, providing decision support for clinicians. In addition, the embodiment of the present disclosure can also use a lookup table method to evaluate and classify the characteristic data, and correspond the acquired characteristic data to the preset classification. The machine learning model can use a dataset including different ST segment feature data as sample data, and use the classification of myocardial ischemia corresponding to the sample data as labels to train the initial machine learning model to obtain a machine learning model suitable for clinical application. Of course, the machine learning model can be a classification model within a main model, and the main model also includes a feature extraction model for extracting ST segment feature data, which is not limited here.

[0052] In this way, by extracting key characteristic data such as ST segment offset and duration, the electrophysiological changes of myocardial ischemia can be directly reflected, providing precise input for subsequent assessments. Using a machine learning model to evaluate and classify characteristic data automatically identifies complex patterns and relationships, improving the accuracy and reliability of myocardial ischemia assessments and reducing human error. Pre-set thresholds and classification criteria provide the machine learning model with a clear basis for judgment, enabling it to quickly output classification results, enhancing the system's real-time performance and responsiveness.

[0053] Optionally, based on the obtained judgment result, a relative scanning operation is performed, including: when the judgment result is that there is no offset or abnormality, continuing the scan; when the judgment result is that the offset is n1mV, or the duration is m1 minute, issuing a prompt message and continuing the scan; the first threshold ≤ n1 ≤ the third threshold, m1 ≤ the fifth threshold; when the judgment result is that the offset is n3mV, or the duration is m3 minutes, terminating the scan; n3>the third threshold, m3>the fifth threshold.

[0054] In the embodiment of the present disclosure, when the judgment result shows that the ST segment has not shifted or is abnormal, the system deems that the patient's myocardial state is normal, and the scanning operation continues without additional intervention. If the judgment result shows that the ST segment shift is between the first threshold and the third threshold, and the duration is less than or equal to the fifth threshold, the system will display a prompt message on the screen to remind medical staff to pay attention to the patient's condition, but the scanning operation will continue. Alternatively, the system will issue an audible and visual alarm to remind medical staff that the patient may be at risk of moderate myocardial ischemia. If the ST segment shift exceeds the third threshold, or the duration exceeds the fifth threshold, the system will automatically terminate the scan, indicating that the patient may be in a state of severe myocardial ischemia, and continuing the scan may cause serious harm to the patient. At this time, the system will force medical staff to perform medical intervention through pop-up windows and sound alarms.

[0055] Optionally, when the judgment result is an offset of n1mV, or a duration of m1 minutes, a prompt message is issued and the scan continues, including: when the judgment result is an offset of n2mV, or a duration of m2 minutes, scanning is performed according to the user's manual confirmation information; the second threshold ≤n2≤the third threshold, the fourth threshold ≤m2≤the fifth threshold.

[0056] In the embodiment of the present disclosure, when the ST segment offset reaches between the second threshold and the third threshold, or the duration is between the fourth threshold and the fifth threshold, the scanning operation will not stop automatically, but will wait for the medical staff to manually confirm based on the actual situation of the patient and decide whether to continue scanning.

[0057] Optionally, when the judgment result is an offset of n2mV, or a duration of m2 minutes, scanning is performed according to the user's manual confirmation information, including: continuing the scanning if confirmation information for continuing the scanning is received within the set time; terminating the scanning if no confirmation information for continuing the scanning is received within the set time.

[0058] In the disclosed embodiment, the patient may be at moderate risk of myocardial ischemia, and manual confirmation information needs to be obtained within a set time to determine whether to continue scanning.

[0059] The judgment ranges and values ​​of n1, n2, n3, m1, m2, and m3 in the above description are only for illustration purposes of the present disclosure and are not actual values. Specific values ​​require a machine learning model to analyze a large amount of historical ECG data to produce appropriate results.

[0060] By implementing different scanning procedures based on the severity of myocardial ischemia, patient safety can be effectively guaranteed during the scan, preventing emergencies caused by worsening myocardial ischemia. Furthermore, this graded response mechanism balances patient safety with scan continuity, avoiding interruptions to necessary examination processes due to excessive intervention and improving medical efficiency.

[0061] Optionally, the scanning method for CT equipment further includes: recording the patient's electrocardiogram data and judgment results in real time; and generating an analysis report based on the electrocardiogram data and judgment results.

[0062] Combine Figure 3 As shown, the embodiment of the present disclosure provides another scanning method for a CT device, comprising:

[0063] S301: The processor obtains the patient's electrocardiogram data.

[0064] S302: The processor detects and analyzes the ST segment of the electrocardiogram data to obtain a judgment result on the severity of the patient's myocardial ischemia.

[0065] S303: The processor performs a relative scanning operation according to the obtained judgment result.

[0066] S304, the processor records the patient's ECG data and judgment results in real time.

[0067] S305: The processor generates an analysis report based on the ECG data and the judgment result.

[0068] In the disclosed embodiment, during the scanning process, the system continuously collects the patient's ECG data and performs real-time analysis on these data to determine the severity of myocardial ischemia. At the same time, the system stores the ECG data and each judgment result in real time in a database or log file to ensure the integrity and traceability of all information. These records include not only the original ECG waveform, but also key information such as ST segment offset, duration, and corresponding ischemia grade. Subsequently, the system automatically generates an analysis report based on the stored ECG data and judgment results. The report content includes the patient's basic information, scanning time, key features of the ECG data (such as ST segment changes, etc.), the judgment results of myocardial ischemia (such as mild, moderate or severe ischemia), and the corresponding measures taken during the scanning process (such as prompts, alarms or termination of the scan). In addition, the report will also provide a detailed interpretation of the myocardial ischemia state, as well as clinical recommendations based on these data to help doctors better understand the patient's heart condition.

[0069] Combine Figure 4As shown, an embodiment of the present disclosure provides a scanning device 40 for a CT device, comprising an ECG data acquisition module 401, an automatic myocardial ischemia determination module 402, and a scanning linkage control module 403. The ECG data acquisition module 401 is configured to acquire ECG data of a patient; the automatic myocardial ischemia determination module 402 is configured to detect and analyze the ST segment of the ECG data to obtain a determination result on the severity of the patient's myocardial ischemia; and the scanning linkage control module 403 is configured to perform a relative scanning operation based on the obtained determination result.

[0070] The scanning device 40 for CT equipment provided in the embodiment of the present disclosure is used to obtain the patient's electrocardiogram (ECG) data in real time, accurately detect and deeply analyze the ST segment in the ECG data, and accurately determine the severity of the patient's myocardial ischemia through careful extraction and quantitative analysis of ST segment features, such as monitoring ST segment offset and duration. The ischemic state can be finely divided into different levels such as mild, moderate, and severe. Based on the determined severity, relative scanning operations are then performed. In this way, by accurately analyzing the patient's characteristic ECG signals, real-time monitoring and intelligent processing of myocardial ischemia can be achieved, preventing the patient from suffering serious harm due to worsening myocardial ischemia during the scanning process.

[0071] Combine Figure 5 As shown, an embodiment of the present disclosure provides a CT device, including: a CT device body 50, and the above-mentioned scanning device 40 for the CT device. The scanning device 40 for the CT device is installed on the CT device body 50. The installation relationship described here is not limited to placement inside the CT device body, but also includes installation connections with other components of the CT device, including but not limited to physical connections, electrical connections or signal transmission connections, etc. Those skilled in the art will understand that the scanning device 40 for the CT device can be adapted to a feasible CT device body 50, thereby realizing other feasible embodiments. The CT device body 50 may include a console and a scanning body connected to the console, and the scanning body may include a scanning bed and a scanning gantry including a detector and a tube. The scanning device 40 may be set on the console.

[0072] The technical solutions of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, among other media capable of storing program code.

[0073] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to also include plural forms. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variations "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, an element defined by the sentence "comprising a..." does not exclude the presence of other identical elements in the process, method or device that includes the element. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments can be referenced to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be found in the description of the method part.

[0074] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. The technicians will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0075] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, and can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of the present disclosure may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0076] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architectures, functions and operations of the systems, methods and computer program products according to the embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A scanning method for CT equipment, characterized in that: include: Obtain the patient's ECG data; Detect and analyze the ST segment of the ECG data to determine the severity of the patient's myocardial ischemia; Based on the obtained judgment result, a relative scanning operation is performed.

2. The scanning method according to claim 1, wherein: Obtain the patient's ECG data, including: Transmitting the collected first-lead ECG data and second-lead ECG data to the console; reconstructing third-lead ECG data based on the received first-lead ECG data and second-lead ECG data; Select the target lead ECG data to determine myocardial ischemia.

3. The scanning method according to claim 1, wherein: Obtain the patient's ECG data, including: Acquiring the patient's first-lead ECG data and second-lead ECG data; Control the underlying ECG data receiving board to calculate and obtain the third-lead ECG data; According to the analysis requirements, some lead ECG data are transmitted to the myocardial ischemia automatic judgment module of the console.

4. The scanning method according to claim 1, wherein: Detect and analyze the ST segment of the ECG data to determine the severity of the patient's myocardial ischemia, including: Extracting characteristic data of the ST segment; wherein the characteristic data includes offset and / or duration; According to the preset thresholds and grading standards, the characteristic data are evaluated and graded using machine learning models or table lookup methods to obtain a judgment result on the severity of the patient's myocardial ischemia.

5. The scanning method according to claim 1, wherein: Based on the obtained judgment results, perform relative scanning operations, including: If it is determined that no deviation or abnormality occurs, the scanning is continued; If the judgment result is an offset of n1mV or a duration of m1 minutes, a prompt message is issued and the scan continues; the first threshold ≤ n1 ≤ the third threshold, m1 ≤ the fifth threshold; If the judgment result is that the deviation is n3 mV, or the duration is m3 minutes, the scan is terminated; n3> the third threshold, m3> the fifth threshold.

6. The scanning method according to claim 5, characterized in that: If the result is an offset of n1mV or a duration of m1 minute, a prompt message is issued and the scan continues, including: When the judgment result is an offset of n2 mV or a duration of m2 minutes, scanning is performed according to the user's manual confirmation information; the second threshold ≤ n2 ≤ the third threshold, and the fourth threshold ≤ m2 ≤ the fifth threshold.

7. The scanning method according to claim 6, characterized in that: When the judgment result is an offset of n2mV or a duration of m2 minutes, the scanning is performed according to the user's manual confirmation information, including: If a confirmation message for continuing scanning is received within the set time, the scanning will continue; If no confirmation message for continuing scanning is received within the set time, the scanning is terminated.

8. The scanning method according to any one of claims 1 to 7, characterized in that: Also includes: Record the patient's ECG data and judgment results in real time; Generate an analysis report based on ECG data and judgment results.

9. A scanning device for CT equipment, characterized in that: include: an ECG data acquisition module, configured to acquire ECG data of a patient; The myocardial ischemia automatic judgment module is configured to detect and analyze the ST segment of the electrocardiogram data to obtain a judgment result on the severity of the patient's myocardial ischemia; The scanning linkage control module is configured to perform a relative scanning operation according to the obtained judgment result.

10. A CT device, characterized in that: include: CT equipment body; The scanning device for CT equipment according to claim 9, mounted on the CT equipment body.

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