Scan triggering method, apparatus, system, and storage medium

Abstract

The application relates to a scan triggering method, device, system and storage medium, wherein the scan triggering method comprises the following steps: acquiring a heart motion signal of a scanning object collected in real time; judging whether the latest signal data in the heart motion signal meets a preset triggering condition; generating a triggering instruction in the case that the latest signal data meets the preset triggering condition; and the triggering instruction is used for triggering a medical imaging device to perform medical scanning on the scanning object. Through the application, the problem that accurate scan triggering cannot be realized is solved, and the heart motion signal collected is used for accurately triggering scanning.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and in particular to scan triggering methods, devices, systems and storage media. Background Technology

[0002] When acquiring cardiac images using medical imaging instruments such as computed tomography (CT) and magnetic resonance imaging (MR), precise real-time triggering of cardiac motion is required.

[0003] In existing methods for detecting cardiac motion, a displacement curve containing information about changes in the volume of the human heart is determined based on the change in distance between the acquisition device and the skin surface. This displacement curve is then differentiated to obtain information such as the time and volume changes of atrial and ventricular contraction and relaxation, which are used for scan triggering. However, the differentiation method used in these methods is not robust to data with respiratory interference and cannot achieve accurate scan triggering.

[0004] There is currently no effective solution to the problem of inaccurate scanning triggering in related technologies. Summary of the Invention

[0005] This embodiment provides a scan triggering method, apparatus, system, and storage medium to solve the problem of inaccurate scan triggering in related technologies.

[0006] Firstly, this embodiment provides a scan triggering method, the method comprising:

[0007] Acquire real-time cardiac motion signals of the scanned object;

[0008] Determine whether the latest signal data in the cardiac motion signal meets the preset triggering conditions;

[0009] If the latest signal data meets the preset triggering conditions, a triggering command is generated; the triggering command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

[0010] In some embodiments, determining whether the latest signal data in the cardiac motion signal meets a preset trigger condition includes:

[0011] According to the preset selection rules, the target data point in the latest signal data is determined;

[0012] Determine the predicted probability corresponding to the target data point; the predicted probability is used to indicate the probability that the target data point is a specific point of the cardiac motion signal.

[0013] Based on the predicted probability, it is determined whether the target data point meets the preset triggering condition; the preset triggering condition refers to the target data point being a specific point of the cardiac motion signal.

[0014] In some embodiments, determining whether the target data point meets the preset triggering condition based on the predicted probability includes:

[0015] The predicted probability of the target data point is compared with a preset probability threshold;

[0016] When the predicted probability of the target data point is greater than the probability threshold, the amplitude of the first waveform corresponding to the target data point is compared with the preset amplitude of the second waveform.

[0017] When the difference between the amplitude of the first waveform and the amplitude of the second waveform is within a preset range, the target data point is determined to meet the preset triggering condition.

[0018] In some embodiments, determining the target data point in the latest signal data according to a preset selection rule includes:

[0019] Extract the latest signal data from the cardiac motion signals;

[0020] The latest signal data is windowed to obtain the corresponding windowed data;

[0021] The target data points in the windowed data are determined according to the preset selection rules.

[0022] In some embodiments, determining the predicted probability corresponding to the target data point includes:

[0023] The target data points are processed using a signal detection model to obtain the predicted probability corresponding to each target data point; wherein, the training of the signal detection model is as follows:

[0024] Multiple cardiac motion signals used for model training are labeled with sample-specific points and non-sample-specific points.

[0025] Based on a preset data window length, the labeled cardiac motion signal is segmented to obtain multiple sample signals;

[0026] Construct sample datasets corresponding to each of the sample signals, and train the signal detection model based on the sample datasets.

[0027] In some embodiments, when the latest signal data meets the preset triggering conditions, a trigger command is generated; the trigger command is used to trigger a medical imaging device to perform a medical scan on the scanned object, including:

[0028] When the target data point is detected as a specific point of the cardiac motion signal, a corresponding trigger command is generated;

[0029] The trigger command is transmitted to the medical imaging device; the trigger command is used to instruct the medical imaging device to perform a medical scan on the object being scanned.

[0030] In some embodiments, acquiring the real-time acquired cardiac motion signal of the scanned object includes:

[0031] The heart movement signals of the scanned object are collected in real time using a radar acquisition device.

[0032] Secondly, this embodiment provides a scan triggering device, the device comprising:

[0033] The acquisition module is used to acquire the real-time cardiac motion signals of the scanned object;

[0034] The judgment module is used to determine whether the latest signal data in the cardiac motion signal meets the preset triggering conditions;

[0035] The triggering module is used to generate a triggering command when the latest signal data meets the preset triggering conditions; the triggering command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

[0036] Thirdly, this embodiment provides a scan triggering system, which includes: an acquisition device, a processing unit, and a medical imaging device; wherein the acquisition device is communicatively connected to the processing unit, and the processing unit is connected to the medical imaging device;

[0037] The acquisition device is used to acquire the cardiac motion signals of the scanned object in real time;

[0038] The processing unit is used to execute the scan triggering method described in the first aspect above.

[0039] Fourthly, this embodiment provides a storage medium storing a computer program that, when executed by a processor, implements the scan triggering method described in the first aspect above.

[0040] Compared with related technologies, the scanning triggering method, apparatus, system, and storage medium provided in this embodiment include a scanning triggering system comprising an acquisition device, a processing unit, and medical imaging equipment. The acquisition device is used to acquire cardiac motion signals of the scanned object in real time. By acquiring the real-time acquired cardiac motion signals of the scanned object, it determines whether the latest signal data in the cardiac motion signals meets preset triggering conditions. If the latest signal data meets the preset triggering conditions, a triggering command is generated. The triggering command is used to trigger the medical imaging equipment to perform a medical scan of the scanned object, solving the problem of inaccurate scanning triggering and realizing accurate scanning triggering using the acquired cardiac motion signals.

[0041] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0043] Figure 1 This is a hardware structure block diagram of a terminal device for a scanning triggering method provided in an embodiment of this application;

[0044] Figure 2 This is a flowchart of a scan triggering method provided in an embodiment of this application;

[0045] Figure 3 This is a structural block diagram of a scan triggering system provided in an embodiment of this application;

[0046] Figure 4 This is a flowchart of a scan triggering method provided in another embodiment of this application;

[0047] Figure 5 This is a schematic flowchart of a scan triggering method provided in an embodiment of this application;

[0048] Figure 6 This is a flowchart illustrating a scan triggering method provided in another embodiment of this application;

[0049] Figure 7 This is a schematic flowchart of a signal detection model training and detection method provided in an embodiment of this application;

[0050] Figure 8 This is a flowchart of a preferred embodiment of the scan triggering method provided in this application;

[0051] Figure 9 This is a structural block diagram of a scanning triggering device provided in an embodiment of this application.

[0052] In the diagram: 102, processor; 104, memory; 106, transmission device; 108, input / output device; 10, acquisition module; 20, judgment module; 30, trigger module. Detailed Implementation

[0053] To better understand the purpose, technical solution, and advantages of this application, the application is described and explained below in conjunction with the accompanying drawings and embodiments.

[0054] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning as understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these,” used in this application, do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to such processes, methods, products, or devices. The terms “connected,” “linked,” and “coupled,” used in this application, are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. The term “multiple” used in this application refers to two or more. The "and / or" operator describes the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: A alone, A and B simultaneously, and B alone. Typically, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," and "third," etc., used in this application are merely for distinguishing similar objects and do not represent a specific ordering of the objects.

[0055] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. For example, it can run on a terminal. Figure 1 This is a hardware structure block diagram of the terminal for the scan triggering method in this embodiment. For example... Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 and a memory 104 for storing data are also included. The processor 102 may be, but is not limited to, a microprocessor (MCU) or a programmable logic device (FPGA). The terminal may also include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that… Figure 1The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown are illustrated.

[0056] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the scan triggering method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, thereby implementing the aforementioned method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0057] The transmission device 106 is used to receive or send data via a network. This network includes a wireless network provided by the terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 can be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0058] This embodiment provides a scan triggering method. Figure 2 This is a flowchart of the scan triggering method in this embodiment, as follows: Figure 2 As shown, the process includes the following steps:

[0059] Step S210: Acquire the real-time cardiac motion signal of the scanned object;

[0060] Step S220: Determine whether the latest signal data in the cardiac motion signal meets the preset triggering conditions;

[0061] Step S230: If the latest signal data meets the preset triggering conditions, a trigger command is generated; the trigger command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

[0062] Specifically, this embodiment applies to scan-triggered systems, such as... Figure 3As shown, the system includes a data acquisition device, a processing unit, and medical imaging equipment. The data acquisition device is communicatively connected to the processing unit, and the processing unit is connected to the medical imaging equipment. The data acquisition device is used to acquire cardiac motion signals of the scanned object in real time. These cardiac motion signals are acquired directly from the surface of the heart or the heart itself. Data acquisition devices such as Doppler radar and radio frequency sensors can be used; however, this embodiment does not limit the specific data acquisition device used.

[0063] Taking a Doppler radar acquisition device as an example, a continuous wave radar signal is transmitted to the thoracic cavity of the scanned object through a radar antenna. The returned echo signal and the transmitted oscillation frequency signal are mixed and processed to extract the simulated cardiac motion signal of the scanned object from the mixing result. The simulated cardiac motion signal extracted by the Doppler radar is impedance matched, and a high-pass filter is used to filter out the DC component in the low-frequency signal. The cutoff frequency of the high-pass filter is preferably 0.25Hz. The processed simulated cardiac motion signal is amplified and then converted into the corresponding digital cardiac motion signal by an analog-to-digital converter. The digital cardiac motion signal is input into a microprocessor. In the microprocessor, the digital cardiac motion signal is subjected to median filtering to remove high-frequency interference, thereby obtaining the cardiac displacement signal waveform after median filtering algorithm processing. The median-filtered signal is then input into a digital signal processing filter. This filter is preferably a second-order infinite impulse response (IIR) digital bandpass filter of 0.5 to 10Hz to filter out other interference signals other than cardiac motion, thus obtaining the final cardiac motion signal.

[0064] The real-time acquired cardiac motion signals of the scanned object are wirelessly transmitted to the processing unit to obtain the latest signal data from the cardiac motion signals. Based on preset selection rules, the target data point in the latest signal data is determined. These selection rules specify the concrete definition of the target data point; for example, the latest data point in the latest signal data may be defined as the target data point, or the data point 0.01 seconds prior to the latest data point may be defined as the target data point.

[0065] Furthermore, the probability that the target data point is a specific point of the cardiac motion signal is predicted, and the corresponding predicted probability is obtained. The specific point of the cardiac motion signal can be a peak point or other pre-selected data points, which can be set by the user according to the actual application requirements. For example, the signal value of the target data point is compared with the set value of the specific point. Based on the comparison result and combined with the signal value change trend of the data points near the target data point, the probability that the target data point is the specific point is predicted; or, the target data point is predicted by a signal detection model, and the predicted probability corresponding to the target data point is output.

[0066] In the training process of the aforementioned signal detection model, multiple cardiac motion signals used for model training are pre-labeled with specific points and without specific points. Based on a preset data window length, such as a two-second window, the labeled cardiac motion signals are segmented to obtain multiple sample signals. A sample dataset corresponding to each sample signal is then constructed. This sample dataset can typically be divided into a training set and a validation set. The signal detection model is then trained based on the sample dataset. It is understood that in this embodiment, the signal detection model can adaptively adjust based on the latest prediction results to better suit the actual application environment and improve the accuracy of probability prediction.

[0067] Next, the predicted probability is compared with a preset probability threshold. When the predicted probability of the target data point is greater than the probability threshold, the amplitude of the first waveform corresponding to the target data point is compared with a preset second waveform amplitude. The preset second waveform amplitude is the theoretical or empirical waveform amplitude corresponding to the specific point. Users can customize the setting according to the general waveform characteristics of cardiac motion signals in actual applications to determine whether the difference between the first and second waveform amplitudes is within a preset range, such as 0.5% of the maximum amplitude difference of the cardiac motion signal. If the difference between the first and second waveform amplitudes is within the preset range, the target data point is determined to meet the preset triggering condition, that is, the target data point is determined to be a specific point of the cardiac motion signal, indicating that the latest signal data meets the preset triggering condition, and a trigger command is generated to trigger the medical imaging equipment to perform a medical scan on the scanned object. In this embodiment, the medical imaging equipment includes, but is not limited to, computed tomography scanners and magnetic resonance imaging equipment.

[0068] It should be noted that, in addition to defining the preset trigger condition as a specific point where the target data point is a cardiac motion signal, it can also be used to determine whether the heart is experiencing abnormal electrical activity corresponding to a specific physiological or pathological event, such as arrhythmia or valvular closure, based on the latest signal data in the cardiac motion signal. When abnormal electrical activity is detected in the heart, a scan is triggered to better observe the cardiac structure in an abnormal state.

[0069] In existing methods for detecting cardiac motion, a displacement curve containing information about changes in the volume of the human heart is determined based on the change in distance between the acquisition device and the skin surface. This displacement curve is then differentiated to obtain information such as the time and volume changes of atrial and ventricular contraction and relaxation, which are used for scan triggering. However, the differentiation method used in these methods is not robust to data with respiratory interference and cannot achieve accurate scan triggering.

[0070] Compared to existing technologies, this application acquires real-time cardiac motion signals from the object being scanned; determines whether the latest signal data in the cardiac motion signals meets preset trigger conditions; and, if the latest signal data meets the preset trigger conditions, triggers the medical imaging equipment to perform a medical scan on the object. Based on this, by acquiring and analyzing accurate cardiac motion signals in real time, and triggering the medical imaging equipment to perform a medical scan on the object when the latest signal data in the cardiac motion signals meets the preset trigger conditions, this solves the problem of inaccurate scan triggering and achieves precise scan triggering using the acquired cardiac motion signals.

[0071] In some of these embodiments, such as Figure 4 As shown, step S220, determining whether the latest signal data in the cardiac motion signal meets the preset triggering conditions, includes the following steps:

[0072] Step S221: Determine the target data point in the latest signal data according to the preset selection rules;

[0073] Step S222: Determine the predicted probability corresponding to the target data point; the predicted probability is used to indicate the probability that the target data point is a specific point of cardiac motion signal.

[0074] Step S223: Based on the predicted probability, determine whether the target data point meets the preset triggering condition; the preset triggering condition refers to the target data point being a specific point of cardiac motion signal.

[0075] Specifically, the latest signal data from cardiac motion signals is acquired, and target data points within this latest signal data are determined according to preset selection rules; or, the latest signal data from cardiac motion signals is windowed to obtain corresponding windowed data, and target data points within the windowed data are determined according to preset selection rules. The selection rules are used to indicate the specific definition of the target data points.

[0076] For example, by using preset rules, the latest data point in the latest signal data is defined as the target data point, or the data point 0.01 seconds before the latest data point is defined as the target data point. In this embodiment, the specific definition of the target data point is not limited and can be set according to actual application requirements.

[0077] This embodiment identifies a target data point in the latest signal data and determines the predicted probability corresponding to that target data point. This predicted probability indicates the probability that the target data point is a specific point of the cardiac motion signal. Based on the predicted probability, it is determined whether the target data point meets preset triggering conditions, thereby accurately determining whether the target data point is a specific point of the cardiac motion signal and improving the accuracy of scan triggering.

[0078] In some embodiments, step S223, determining whether the target data point meets the preset triggering condition based on the predicted probability, includes the following steps:

[0079] The predicted probability of the target data point is compared with a preset probability threshold.

[0080] When the predicted probability of the target data point is greater than the probability threshold, the amplitude of the first waveform corresponding to the target data point is compared with the preset amplitude of the second waveform.

[0081] When the difference between the amplitude of the first waveform and the amplitude of the second waveform is within a preset range, the target data point is determined to meet the preset triggering condition.

[0082] Specifically, the predicted probability of the target data point is compared with a preset probability threshold to determine whether the predicted probability of the target data point is greater than the probability threshold. When the predicted probability of the target data point is detected to be greater than the probability threshold, the amplitude of the first waveform corresponding to the target data point is compared with a preset second waveform amplitude. The preset second waveform amplitude is the theoretical or empirical waveform amplitude corresponding to the specific point, which can be customized by the user according to the general waveform characteristics of cardiac motion signals in actual applications. If the difference between the first waveform amplitude and the second waveform amplitude is detected to be within a preset range, the target data point is determined to meet the preset triggering condition, that is, the target data point is a specific point of the cardiac motion signal. The specific point of the cardiac motion signal can be a peak point or other pre-selected data points.

[0083] Taking the selection of a peak point as a specific point in the cardiac motion signal as an example, when the predicted probability of the target data point being a peak point is greater than a probability threshold, the waveform amplitude corresponding to the target data point is compared with the waveform amplitude corresponding to the peak point to determine whether the difference between the two waveform amplitudes is within a preset range, such as 0.5% of the maximum amplitude difference of the cardiac motion signal. If the difference between the two waveform amplitudes is within the preset range, the target data point is determined to be a peak point of the cardiac motion signal, indicating that the current target data point meets the preset triggering conditions.

[0084] In this embodiment, the predicted probability of the target data point is compared with a preset probability threshold. When the predicted probability of the target data point is greater than the probability threshold, the amplitude of the first waveform corresponding to the target data point is compared with the preset second waveform amplitude. When the difference between the amplitude of the first waveform and the amplitude of the second waveform is within a preset range, the target data point is determined to meet the preset triggering condition, thereby achieving accurate analysis of whether the target data point is a specific point of the cardiac motion signal.

[0085] In some embodiments, step S221, determining the target data point in the latest signal data according to a preset selection rule, includes the following steps:

[0086] Extract the latest signal data from cardiac motion signals;

[0087] The latest signal data is windowed to obtain the corresponding windowed data;

[0088] Based on the preset selection rules, the target data points in the windowed data are determined.

[0089] Specifically, the latest signal data is extracted from the received cardiac motion signals. This latest signal data is then windowed according to a preset data window length to obtain corresponding windowed data, which is then normalized. It should be noted that this embodiment uses a preset duration as the window for data windowing, for example, a preset duration of 2 seconds. Data acquisition follows the principle of sampling one by one and real-time transmission; that is, each data point acquired is filled into the window of the current preset duration. Once the window is full, i.e., the accumulated duration reaches the preset duration, the current windowed data is further processed to ensure data continuity and real-time performance.

[0090] For example, the latest extracted signal data is windowed according to the latest two-second data to obtain two-second window data. The windowed data is then normalized according to [-1,1] to map the numerical range of the windowed data to the range [-1,1].

[0091] Furthermore, based on preset selection rules, target data points in the windowed data are determined. These preset selection rules specify the exact definition of the target data points; for example, the latest data point in the latest signal data can be defined as the target data point, or the data point 0.01 seconds before the latest data point can be defined as the target data point.

[0092] In this embodiment, the latest signal data in cardiac motion signals is extracted, windowed data is applied to the latest signal data to obtain corresponding windowed data, and target data points in the windowed data are determined according to preset selection rules. This improves the accuracy of data processing while minimizing the computational load in the data processing process through windowing, thereby enhancing efficiency.

[0093] In some embodiments, determining the prediction probability corresponding to the target data point in step S222 includes the following steps:

[0094] The target data points are processed using a signal detection model to obtain the predicted probabilities corresponding to the target data points; the training of the signal detection model is as follows:

[0095] Multiple cardiac motion signals used for model training are labeled with sample-specific points and non-sample-specific points.

[0096] Based on a preset data window length, the labeled cardiac motion signal is segmented to obtain multiple sample signals;

[0097] Construct sample datasets corresponding to each sample signal, and train the signal detection model based on the sample datasets.

[0098] Specifically, multiple cardiac motion signals are acquired for model training. These signals are then subjected to median filtering to remove high-frequency interference. Each median-filtered cardiac motion signal is then labeled with specific points (1) and non-specific points (0). Specifically, specific points and their vicinity are labeled as 1, while other non-specific points are labeled as 0. For example, if a specific point is a peak, the peak and its vicinity are labeled as 1, and other non-peak points are labeled as 0. The multiple cardiac motion signals used for model training can be from different scanned objects or from multiple scans of the same object; there is no limitation on this method.

[0099] Furthermore, based on the preset data window length, such as a two-second window, the labeled cardiac motion signal is segmented to obtain multiple sample signals. Each sample signal is normalized according to [-1,1], and a sample dataset corresponding to each sample signal is constructed. This sample dataset can be divided into a training set and a validation set. The signal detection model is trained based on the sample dataset to obtain the optimal signal detection model parameters.

[0100] It should be noted that the signal detection model trained above is used to predict the probability value of the target data point in the actual collected cardiac motion signal being a specific point. The signal detection model can be adaptively adjusted according to the latest prediction results to better adapt to the actual application environment and improve the accuracy of probability prediction.

[0101] In this embodiment, multiple cardiac motion signals used for model training are labeled with specific points and non-specific points. Based on a preset data window length, the labeled cardiac motion signals are segmented to obtain multiple sample signals. A sample dataset corresponding to each sample signal is constructed, and the signal detection model is trained based on the sample dataset. Thus, the signal detection model can accurately predict whether a target data point is a specific point of a cardiac motion signal, while also exhibiting strong robustness.

[0102] In some embodiments, step S230 involves generating a trigger command when the latest signal data meets preset trigger conditions; the trigger command is used to trigger the medical imaging device to perform a medical scan on the scanned object, and includes the following steps:

[0103] When a specific point in the target data is detected as a cardiac motion signal, a corresponding trigger command is generated;

[0104] The trigger command is transmitted to the medical imaging equipment; the trigger command is used to instruct the medical imaging equipment to perform a medical scan on the object being scanned.

[0105] Specifically, when a target data point is detected as a specific point of cardiac motion signal, a trigger command is generated and transmitted to the medical imaging equipment to instruct the medical imaging equipment to perform a medical scan on the object being scanned.

[0106] It should be noted that the aforementioned medical imaging equipment includes, but is not limited to, computed tomography scanners and magnetic resonance imaging devices. While transmitting trigger commands to instruct the medical imaging equipment to perform a scan, the display terminal displays the current cardiac motion signals and the data points that triggered the scan in real time. This visualizes the scan trigger points of the medical imaging equipment for user reference and confirmation, ensuring the accuracy of the scan trigger.

[0107] In this embodiment, when a target data point is detected as a specific point of cardiac motion signal, a corresponding trigger command is generated and transmitted to the medical imaging equipment. This trigger command is used to instruct the medical imaging equipment to perform a medical scan on the object being scanned, thereby realizing the real-time and accurate triggering of the scan using cardiac motion signals.

[0108] In some embodiments, acquiring the real-time cardiac motion signal of the scanned object includes the following steps:

[0109] The radar acquisition device collects the heart movement signals of the scanned object in real time.

[0110] Specifically, the data acquisition device can be a radar acquisition device, a radio frequency sensor, etc. Among them, the radar acquisition device includes, but is not limited to, Doppler radar, frequency modulated continuous wave radar and ultra-wideband radar, and this embodiment does not limit the specific acquisition device used.

[0111] For example, a Doppler radar acquisition device is used for signal acquisition. A continuous wave radar signal is transmitted to the thoracic cavity of the scanned object via a radar antenna. The echo signal and the transmitted oscillation frequency signal are mixed, and the simulated cardiac motion signal of the scanned object is extracted from the mixing result. Impedance matching is performed on the simulated cardiac motion signal extracted by the Doppler radar, and a high-pass filter is used to filter out the DC component in the low-frequency signal. The cutoff frequency of the high-pass filter is preferably 0.25Hz. The processed simulated cardiac motion signal is amplified and then converted into a corresponding digital cardiac motion signal by an analog-to-digital converter. Further, the digital cardiac motion signal is input into a microprocessor, where median filtering is performed to remove high-frequency interference. The median-filtered signal is then input into a digital signal processing filter, preferably an IIR digital bandpass filter of 0.5 to 10Hz, to filter out other interference signals besides cardiac motion, resulting in the final cardiac motion signal. It should be noted that the Doppler radar used in this embodiment can perform non-contact cardiac motion signal monitoring under high magnetic fields, avoiding the cumbersome electrode patching process. At the same time, Doppler radar can penetrate human tissue and directly collect signals from the surface of the heart or the heart body to detect the movement of the left and right ventricles of the heart, thereby providing more accurate cardiac motion signals.

[0112] In this embodiment, the heart motion signal of the scanned object is collected in real time using a radar acquisition device, ensuring the accuracy of the acquired heart motion signal while acquiring it non-contactly.

[0113] The present embodiment will be described and explained below through specific examples.

[0114] Figure 5 This is a flowchart illustrating the scan triggering method of this embodiment, as shown below. Figure 5 As shown, the scan triggering method specifically includes the following steps:

[0115] The patient to be scanned lies inside the medical imaging equipment, and the Doppler radar antenna is placed in the middle or slightly above the middle of the patient's chest. At the Doppler radar heartbeat acquisition front end, a continuous wave radar signal is transmitted into the patient's chest cavity through the radar antenna, and a corresponding echo signal S501 is returned. The echo signal and the transmitted oscillation frequency signal are mixed, and the human heart motion signal is extracted from them S502. The heart motion signal extracted by the Doppler radar is impedance matched, and a high-pass filter with a cutoff frequency of 0.25Hz is used to filter out the DC component in the low-frequency signal. The processed heart motion signal is amplified, and then converted into a corresponding digital heart motion signal by an AD converter S503.

[0116] Furthermore, the digital cardiac motion signal is input to the microprocessor S504. In the microprocessor, the digital cardiac motion signal is processed by median filtering to remove high-frequency interference, resulting in a cardiac displacement signal waveform after median filtering algorithm. The median-filtered signal is then passed through a second-order IIR digital bandpass filter of 0.5-10Hz to filter out other interference signals that are not related to cardiac motion.

[0117] Next, the processed Doppler radar heartbeat signal is wirelessly transmitted to the AI ​​algorithm intelligent processing terminal S505. The heartbeat signal is windowed according to the latest two-second data, and the current two-second window data includes the data of the latest point. Data preprocessing is performed on the two-second window data, that is, the two-second window data is normalized according to [-1,1]. Doppler radar heartbeat signals of a large number of people are acquired and preprocessed S506. The signal detection model is trained with the preprocessed Doppler radar heartbeat signals S507, resulting in the trained signal detection model S508. The normalized two-second window data is sent to the trained signal detection model, which can calculate for each data point in the two-second window data. Then, through the trained signal detection model, the predicted probability of each data point in the two-second window data being a peak point is calculated and output. Based on the probability judgment of the current data point and the post-processing judgment of whether the waveform amplitude after median filtering of the current data point is a peak, it is determined whether the current data point is a peak trigger point S509. When the current data point is detected as a peak trigger point, the current data point and the cardiac motion waveform are transmitted to the imaging device display and trigger terminal to realize waveform display and cardiac trigger scanning S510.

[0118] Figure 6 This is a flowchart illustrating the scan triggering method of this embodiment, as shown below. Figure 6 As shown, the scan triggering method specifically includes the following steps:

[0119] The Doppler radar antenna is placed in the middle or slightly above the middle of the patient's chest (S601). A continuous wave radar signal is transmitted into the chest cavity through the antenna. The returned echo signal and the transmitted oscillation frequency signal are mixed, and the cardiac motion signal is extracted from them (S602). Impedance matching is performed on the cardiac motion signal extracted by the Doppler radar. A high-pass filter with a cutoff frequency of 0.25Hz is used to filter out the DC component in the low-frequency signal (S603). The processed cardiac motion signal is then amplified (S604). The amplified cardiac motion signal is then converted into a corresponding digital cardiac motion signal by an AD converter (S605).

[0120] Further, the digital cardiac motion signal is input into the microprocessor for processing (S606). After median filtering to remove high-frequency interference, the signal passes through a 0.5-10Hz second-order IIR digital bandpass filter to remove other interference signals not related to cardiac motion. Then, the real-time cardiac motion signal is windowed based on the latest two-second data, with the current two-second window containing the latest data point (S607). The two-second window data is then preprocessed by normalizing it to [-1,1] (S608).

[0121] S609 Acquires and preprocesses Doppler radar heartbeat signals from a large population. The preprocessed Doppler radar heartbeat signals are then used to train a signal detection model, resulting in a trained signal detection model. S610 The preprocessed two-second window of data is fed into the trained signal detection model. S611 This model can calculate the probability that each data point in the two-second window is a peak point. S612 Based on the probability of the current data point and the post-processing judgment of whether the waveform amplitude after median filtering is a peak, it is determined whether the current data point is a peak trigger point. S613 When the current data point is detected as a peak trigger point, the current data point and the cardiac motion waveform are transmitted to the imaging device display and trigger terminal, realizing waveform display and cardiac-triggered scanning.

[0122] Figure 7 This is a flowchart illustrating the signal detection model training and detection method in this embodiment, as shown below. Figure 7 As shown, the method specifically includes the following steps:

[0123] A large number of cardiac motion signal samples S710 from different populations, including data from individuals with different heart rates, were pre-acquired. The cardiac motion signal samples were then subjected to median filtering to remove high-frequency interference S720. The processed cardiac motion signals were initially labeled with 1 at and around the peak values, and 0 at non-peak values. The cardiac motion signals and labels were then segmented according to a two-second data window to complete the construction of data sample features and labels, resulting in multiple cardiac motion signal samples S730. Each cardiac motion signal sample was normalized to [-1, 1]. The cardiac motion signal samples and labels were then divided into training and validation sets to train and validate the signal detection model, thereby obtaining the optimal model parameters S740.

[0124] In practical applications, Doppler cardiac motion signals from patients are acquired in real time (S750). The acquired Doppler cardiac motion signals are then subjected to median filtering, and the filtered data is further processed through a second-order IIR digital bandpass filter (S760) in the 0.5-10Hz range. Further, the input signal features are extracted using a sliding window approach, specifically by truncating the filtered signal according to the latest two-second data window (S770). The truncated two-second data window is then normalized to [-1,1] (S780). Finally, the normalized data is analyzed and calculated using a trained signal detection model to obtain the predicted probability that the current data point is the peak value (S790).

[0125] The present embodiment will now be described and illustrated through preferred embodiments.

[0126] Figure 8 This is a flowchart of the scan triggering method of this preferred embodiment, as shown below. Figure 8 As shown, the scan triggering method includes the following steps:

[0127] Step S810: Input the real-time acquired cardiac motion signal of the scanned object into the processing unit to extract the latest signal data from the cardiac motion signal;

[0128] Step S820: Window the latest signal data to obtain the corresponding windowed data, and determine the target data point in the windowed data according to the preset selection rules;

[0129] Step S830: The target data point is processed by the signal detection model to obtain the predicted probability corresponding to the target data point; the predicted probability is used to indicate the probability that the target data point is a specific point of cardiac motion signal.

[0130] Step S840: Based on the predicted probability, determine whether the target data point meets the preset triggering condition; the preset triggering condition refers to the target data point being a specific point of cardiac motion signal.

[0131] Step S850: If the latest signal data meets the preset triggering conditions, the medical imaging equipment is triggered to perform a medical scan on the object being scanned.

[0132] In this embodiment, the real-time acquired cardiac motion signals of the scanned object are input into the processing unit. The latest signal data from the cardiac motion signals is extracted, and windowed data is applied to the latest signal data to obtain corresponding windowed data. Target data points in the windowed data are determined according to preset selection rules. These target data points are then processed by a signal detection model to obtain the predicted probability that the target data point is a specific point of the cardiac motion signal. Based on the predicted probability, it can be determined whether the target data point meets preset triggering conditions. If the latest signal data meets the preset triggering conditions, the medical imaging equipment is triggered to perform a medical scan on the scanned object. This solves the problem of inaccurate scan triggering and achieves non-contact acquisition of the cardiac motion signals of the scanned object, avoiding the use of acquisition devices that require direct contact with the skin surface of the scanned object. Simultaneously, the acquired cardiac motion signals are used to accurately trigger the scan.

[0133] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0134] This embodiment also provides a scan triggering device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. The terms "module," "unit," "subunit," etc., used below refer to combinations of software and / or hardware that implement a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0135] Figure 9 This is a structural block diagram of the scanning triggering device in this embodiment, as shown below. Figure 9 As shown, the device includes:

[0136] The acquisition module 10 is used to acquire the cardiac motion signal of the scanned object in real time;

[0137] The judgment module 20 is used to determine whether the latest signal data in the cardiac motion signal meets the preset trigger conditions;

[0138] The trigger module 30 is used to generate a trigger command when the latest signal data meets the preset trigger conditions; the trigger command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

[0139] The device provided in this embodiment acquires the cardiac motion signal of the scanned object in real time. The cardiac motion signal is acquired by the acquisition device. It determines whether the latest signal data in the cardiac motion signal meets the preset trigger conditions. If the latest signal data meets the preset trigger conditions, a trigger command is generated. The trigger command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object. This solves the problem of not being able to achieve accurate scan triggering and realizes accurate scan triggering using the acquired cardiac motion signal.

[0140] In some embodiments, the judgment module 20 is further configured to determine the target data point in the latest signal data according to a preset selection rule; determine the prediction probability corresponding to the target data point; the prediction probability is used to indicate the probability that the target data point is a specific point of the cardiac motion signal; and determine whether the target data point meets the preset triggering condition according to the prediction probability; the preset triggering condition refers to the target data point being a specific point of the cardiac motion signal.

[0141] In some embodiments, the judgment module 20 is further configured to compare the predicted probability of the target data point with a preset probability threshold; when the predicted probability of the target data point is greater than the probability threshold, compare the first waveform amplitude corresponding to the target data point with a preset second waveform amplitude; when the difference between the first waveform amplitude and the second waveform amplitude is within a preset range, determine that the target data point meets the preset triggering condition.

[0142] In some embodiments, the judgment module 20 is further configured to extract the latest signal data from the cardiac motion signal; perform windowing processing on the latest signal data to obtain corresponding windowed data; and determine the target data point in the windowed data according to a preset selection rule.

[0143] In some embodiments, the judgment module 20 is further configured to process the target data point through a signal detection model to obtain the predicted probability corresponding to the target data point; wherein, the training of the signal detection model is as follows: multiple cardiac motion signals used for model training are labeled with sample-specific points and non-sample-specific points; the labeled cardiac motion signals are segmented based on a preset data window length to obtain multiple sample signals; a sample dataset corresponding to each sample signal is constructed, and the signal detection model is trained based on the sample dataset.

[0144] In some embodiments, the trigger module 30 is further configured to generate a corresponding trigger command when the target data point is detected as a specific point of cardiac motion signal; transmit the trigger command to the medical imaging device; and instruct the medical imaging device to perform a medical scan on the scanned object.

[0145] In some embodiments, the acquisition module 10 is also used to acquire the cardiac motion signal of the scanned object in real time via a radar acquisition device.

[0146] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0147] This embodiment also provides a scan triggering system, which includes an acquisition device, a processing unit, and a medical imaging device; wherein the acquisition device is communicatively connected to the processing unit, and the processing unit is connected to the medical imaging device;

[0148] Acquisition device, used to acquire real-time cardiac motion signals of the scanned object;

[0149] The processing unit is used to execute the steps in any of the above method embodiments.

[0150] Optionally, in this embodiment, the above-described processing can be configured to be performed by a computer program using the following steps:

[0151] S1, acquire the real-time cardiac motion signal of the scanned object;

[0152] S2, determine whether the latest signal data in the cardiac motion signal meets the preset trigger conditions;

[0153] S3 generates a trigger command when the latest signal data meets the preset trigger conditions; the trigger command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

[0154] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0155] Furthermore, in conjunction with the scan triggering methods provided in the above embodiments, this embodiment can also provide a storage medium for implementation. The storage medium stores a computer program; when executed by a processor, the computer program implements any of the scan triggering methods described in the above embodiments.

[0156] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0157] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0158] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0159] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A scan triggering method, characterized in that, The method includes: Acquire real-time cardiac motion signals of the scanned object; Determine whether the latest signal data in the cardiac motion signal meets the preset triggering conditions; The step of determining whether the latest signal data in the cardiac motion signal meets the preset triggering condition includes: determining a target data point in the latest signal data according to a preset selection rule; determining the prediction probability corresponding to the target data point; the prediction probability is used to indicate the probability that the target data point is a specific point of the cardiac motion signal; and determining whether the target data point meets the preset triggering condition based on the prediction probability; the preset triggering condition refers to the target data point being a specific point of the cardiac motion signal. The step of determining whether the target data point meets the preset triggering condition based on the predicted probability includes: comparing the predicted probability of the target data point with a preset probability threshold; when the predicted probability of the target data point is greater than the probability threshold, comparing the first waveform amplitude corresponding to the target data point with a preset second waveform amplitude; and determining that the target data point meets the preset triggering condition when the difference between the first waveform amplitude and the second waveform amplitude is within a preset range. If the latest signal data meets the preset triggering conditions, a triggering command is generated; the triggering command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

2. The scan triggering method according to claim 1, characterized in that, The step of determining the target data point in the latest signal data according to a preset selection rule includes: Extract the latest signal data from the cardiac motion signals; The latest signal data is windowed to obtain the corresponding windowed data; The target data points in the windowed data are determined according to the preset selection rules.

3. The scan triggering method according to claim 1, characterized in that, Determining the predicted probability corresponding to the target data point includes: The target data points are processed using a signal detection model to obtain the predicted probability corresponding to each target data point; wherein, the training of the signal detection model is as follows: Multiple cardiac motion signals used for model training are labeled with sample-specific points and non-sample-specific points. Based on a preset data window length, the labeled cardiac motion signal is segmented to obtain multiple sample signals; Construct sample datasets corresponding to each of the sample signals, and train the signal detection model based on the sample datasets.

4. The scan triggering method according to claim 1, characterized in that, When the latest signal data meets the preset triggering conditions, a trigger command is generated; The triggering command is used to trigger the medical imaging equipment to perform a medical scan on the object being scanned, including: When the target data point is detected as a specific point of the cardiac motion signal, a corresponding trigger command is generated; The trigger command is transmitted to the medical imaging device; the trigger command is used to instruct the medical imaging device to perform a medical scan on the object being scanned.

5. The scan triggering method according to claim 1, characterized in that, The acquisition of the real-time collected cardiac motion signal of the scanned object includes: The heart movement signals of the scanned object are collected in real time using a radar acquisition device.

6. A scanning triggering device, characterized in that, The device includes: The acquisition module is used to acquire the real-time cardiac motion signals of the scanned object; The judgment module is used to determine whether the latest signal data in the cardiac motion signal meets the preset triggering conditions; The judgment module is further configured to determine a target data point in the latest signal data according to a preset selection rule; determine the prediction probability corresponding to the target data point; the prediction probability is used to indicate the probability that the target data point is a specific point of the cardiac motion signal; and determine whether the target data point meets the preset triggering condition according to the prediction probability; the preset triggering condition refers to the target data point being a specific point of the cardiac motion signal. The judgment module is further configured to compare the predicted probability of the target data point with a preset probability threshold; when the predicted probability of the target data point is greater than the probability threshold, compare the first waveform amplitude corresponding to the target data point with a preset second waveform amplitude; when the difference between the first waveform amplitude and the second waveform amplitude is within a preset range, determine that the target data point meets the preset triggering condition. The triggering module is used to generate a triggering command when the latest signal data meets the preset triggering conditions; the triggering command is used to trigger the medical imaging equipment to perform a medical scan on the scanned object.

7. A scanning triggering system, characterized in that, The system includes: a data acquisition device, a processing unit, and medical imaging equipment; wherein the data acquisition device is communicatively connected to the processing unit, and the processing unit is connected to the medical imaging equipment; The acquisition device is used to acquire the cardiac motion signals of the scanned object in real time; The processing unit is used to execute the scan triggering method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the scan triggering method according to any one of claims 1 to 5.

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