Image reconstruction method and device, computer device and storage medium

Abstract

The application relates to an image reconstruction method and device, computer equipment and a storage medium. The method comprises the following steps: in response to at least one image reconstruction task, determining a target device from a trusted device list of a magnetic resonance system; the trusted device list comprises image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system; and assigning each image reconstruction task to the target device to instruct the target device to perform each image reconstruction task. In this way, the reconstruction resources of the image reconstruction devices inside the magnetic resonance system and the image reconstruction devices outside the magnetic resonance system are integrated, the reconstruction resource barriers between magnetic resonance systems are broken, more image reconstruction devices do not need to be added, the image reconstruction speed of the magnetic resonance system is improved, and the reconstruction cost is reduced. In addition, the method does not change the original operation mechanism and principle of the magnetic resonance system, and the magnetic resonance imaging effect is not affected.

Description

Technical Field

[0001] This application relates to the field of magnetic resonance imaging technology, and in particular to an image reconstruction method, apparatus, computer equipment, and storage medium. Background Technology

[0002] With the development of magnetic resonance technology, in order to improve the quality of reconstructed images, the receiving coil can use a multi-channel method to acquire magnetic resonance signals in parallel, resulting in a multiple increase in the acquired K-space data. Image reconstruction equipment needs a powerful central processing unit (CPU) or graphics processing unit (GPU) to provide sufficient computing power to acquire magnetic resonance images and extract relevant information in a sufficiently short time to complete the image reconstruction task.

[0003] In related technologies, in order to speed up reconstruction, more reconstruction computers need to be equipped in the magnetic resonance system, which is costly and cannot guarantee that the computing performance of the magnetic resonance system will be fully utilized. Summary of the Invention

[0004] Therefore, it is necessary to provide an image reconstruction method, apparatus, computer equipment, and storage medium that can integrate the available resources of a magnetic resonance system to improve the reconstruction capability of the magnetic resonance system, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides an image reconstruction method, the method comprising:

[0006] In response to at least one image reconstruction task, a target device is determined from a list of trusted devices of the magnetic resonance system; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0007] Each image reconstruction task is assigned to the target device to instruct the target device to perform each image reconstruction task.

[0008] In one embodiment, determining the target device from a list of trusted devices for the magnetic resonance system includes:

[0009] Obtain the first candidate device that is on the same local area network as the magnetic resonance system;

[0010] Based on the list of trusted devices, a trust check is performed on the first candidate device to determine the target device.

[0011] In one embodiment, acquiring a first candidate device located on the same local area network as the magnetic resonance system includes:

[0012] Acquire the operating status of image reconstruction equipment located on the same local area network as the magnetic resonance system; the operating status is used to indicate whether the image reconstruction equipment is idle.

[0013] Image reconstruction devices that are in an idle state are identified as the first candidate devices.

[0014] In one embodiment, the trusted device list also includes the priority of each image reconstruction device;

[0015] Based on the list of trusted devices, a trust check is performed on the first candidate device to determine the target device, including:

[0016] From the first candidate devices, determine the second candidate device that belongs to the trusted device list;

[0017] The target device is determined from the second candidate devices based on their priority.

[0018] In one embodiment, assigning image reconstruction tasks to a target device includes:

[0019] Obtain the computing power requirements for each image reconstruction task and the computing power level of the target device;

[0020] Based on the computing power requirements and computing power level, each image reconstruction task is assigned to the target device.

[0021] In one embodiment, the method further includes:

[0022] Acquire first device information of the image reconstruction equipment inside the magnetic resonance system, and second device information of the image reconstruction equipment outside the magnetic resonance system;

[0023] Based on the first device information and the second device information, create a list of trusted devices for the magnetic resonance system.

[0024] In one embodiment, the method further includes:

[0025] Obtain device information for multiple image reconstruction devices located on the same local area network as the magnetic resonance system;

[0026] The list of trusted devices for the magnetic resonance imaging system is updated based on the device information of each image reconstruction device.

[0027] Secondly, this application also provides an image reconstruction apparatus, which includes:

[0028] The device selection module is used to determine the target device from the trusted device list of the magnetic resonance system in response to at least one image reconstruction task; the trusted device list includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0029] The task allocation module is used to assign each image reconstruction task to the target device, so as to instruct the target device to perform each image reconstruction task.

[0030] Thirdly, this application also provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the method embodiments in the first aspect described above.

[0031] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the method embodiments in the first aspect described above.

[0032] Fifthly, this application also provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of any of the method embodiments in the first aspect described above.

[0033] The aforementioned image reconstruction method, apparatus, computer equipment, and storage medium, in response to at least one image reconstruction task, determine a target device from a list of trusted devices within the magnetic resonance system (MRI) system. This list includes both image reconstruction devices within and outside the MRI system. Each image reconstruction task is then assigned to the target device, instructing it to perform each task. In other words, this application integrates the reconstruction resources of both internal and external image reconstruction devices within the MRI system. Any trusted image reconstruction device can perform a portion of the MRI system's image reconstruction tasks. This breaks down the barriers to reconstruction resources between different MRI systems, allowing for resource sharing without requiring additional image reconstruction devices within the MRI system. This improves the image reconstruction speed and reduces the equipment investment cost. Furthermore, this method integrates the reconstruction resources of image reconstruction devices without adding extra equipment within the MRI system, thus preserving the original operating mechanism and principles of the MRI system and ensuring that the MRI imaging effect remains unaffected. Attached Figure Description

[0034] Figure 1 This is a diagram illustrating the application environment of an image reconstruction method in one embodiment;

[0035] Figure 2 This is a flowchart illustrating an image reconstruction method in one embodiment;

[0036] Figure 3 This is a schematic diagram of the target device selection process in one embodiment;

[0037] Figure 4This is a schematic diagram of the allocation process for image reconstruction tasks in one embodiment;

[0038] Figure 5 This is a flowchart illustrating a method for creating a list of trusted devices in one embodiment;

[0039] Figure 6 This is a flowchart illustrating a trusted device list update method in one embodiment;

[0040] Figure 7 This is a structural block diagram of an image reconstruction apparatus in one embodiment;

[0041] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0043] Magnetic Resonance Imaging (MRI), as a high-resolution imaging technique, acquires an extremely large amount of data, making data processing and image reconstruction complex, and consequently resulting in long image reconstruction times. In some cases, when multiple scans are required, excessive reconstruction processes may cause the image reconstruction equipment to crash. In other cases, physicians need to use the results of previous scans to decide whether to perform subsequent scans, and excessive reconstruction time will extend the overall examination time.

[0044] While rapid imaging technology has improved imaging speed, it has also led to some compromises in image quality. For MRI scans of lesions in specific locations, extremely clear and accurate medical images are still required. In such cases, it is necessary to improve the imaging capabilities and efficiency of the MRI system to complete image reconstruction more quickly and reduce the time cost of MRI.

[0045] Typically, the image reconstruction section of an MRI system consists of one to three reconstruction computers, each dedicated to that specific MRI system. Therefore, the more reconstruction computers a system has, the stronger its image reconstruction capabilities, and consequently, the shorter the time required to complete the image reconstruction task.

[0046] In pursuit of faster image reconstruction speeds to advance treatment and research, institutions such as hospitals, industrial equipment manufacturers, and research institutes have had to equip their MRI systems with more reconstruction computers or purchase more expensive reconstruction computers. This has led to an increasing number of devices in MRI systems, making the entire system more and more redundant. Computational resources cannot be used effectively, and the financial cost of building MRI systems is also high. Furthermore, when problems occur, the large number of devices makes it difficult to accurately locate and troubleshoot the faults.

[0047] Based on this, this application provides an image reconstruction method that improves the reconstruction capabilities of an MRI system without increasing its monetary cost. Specifically, it breaks down the barriers to reconstruction resources between MRI systems, allowing them to share and utilize their resources. Simultaneously, it opens up the execution permissions for image reconstruction tasks within the MRI system, enabling the MRI system to utilize all trusted computer devices with image reconstruction capabilities and share their reconstruction resources. This improves the reconstruction capabilities of the MRI system, accelerates image reconstruction speed, and ensures image reconstruction quality.

[0048] The image reconstruction method provided in this application can be applied to, for example... Figure 1 In the application environment shown, the image reconstruction system 100 includes at least a scanning device 111 and an image reconstruction device 112 in each magnetic resonance system 110. Outside the magnetic resonance system, there are also computer devices 120, which possess image reconstruction capabilities and can be used as image reconstruction devices. Furthermore, the scanning device 111 inside the magnetic resonance system can communicate with the image reconstruction device 112 via wired or wireless means; the devices inside the magnetic resonance system can also communicate with the computer devices 120 outside the magnetic resonance system via a network to assign image reconstruction tasks to the computer devices 120 outside the magnetic resonance system for processing.

[0049] It should be understood that, Figure 1 The illustration only uses two magnetic resonance systems and three external computer devices. In practical applications, more magnetic resonance systems 110 and / or external computer devices 120 can be added to the image reconstruction system 100 to introduce more image reconstruction devices and integrate more reconstruction resources.

[0050] In some embodiments, the scanning device 111 may be a non-invasive biomedical imaging device for disease diagnosis or research purposes, such as a single-modal scanner and / or a multimodal scanner. The single-modal scanner may include, for example, an ultrasound scanner, an X-ray scanner, a CT scanner, a magnetic resonance imaging (MRI) scanner, an ultrasound examination device, an optical coherence tomography (OCT) scanner, an ultrasound (Ultra Sound, US) scanner, an intravascular ultrasound (IVUS) scanner, a near-infrared spectroscopy (NIRS) scanner, a far-infrared (FIR) scanner, or any combination thereof. The multimodal scanner may include, for example, an X-ray imaging-magnetic resonance imaging (X-MRI) scanner, a single-photon emission computed tomography-magnetic resonance imaging (SPECT-MRI) scanner, a positron emission tomography-computed tomography (PET-CT) scanner, a digital subtraction angiography-magnetic resonance imaging (DSA-MRI) scanner, etc. It should be understood that the scanners provided above are for illustrative purposes only and are not intended to limit the scope of this application.

[0051] As an example, scanning device 111 may specifically include a frame, a detector, a detection area, a scanning bed, and a radiation source. The frame can be used to support the detector and the radiation source; the scanning bed can be used to place the target object for scanning; the radiation source can emit radiation towards the target object to irradiate it; and the detector can be used to receive radiation passing through the target object. The target object can be a human body or other animal.

[0052] Optionally, the scanning device 111 may also include modules and / or components for performing imaging and / or related analyses. For example, the scanning device 111 may include a processor that can perform image reconstruction tasks.

[0053] In some embodiments, the scanning device 111 may also send the acquired scanning data to the image reconstruction device 112 via a network for further analysis, processing and display, and / or send the acquired scanning data to a computer device 120 outside the magnetic resonance system via a network for analysis, processing and display.

[0054] As an example, the image reconstruction equipment (including the image reconstruction equipment 112 inside each magnetic resonance system and the computer equipment 120 outside the magnetic resonance system) can be a terminal or a server. The terminal can be various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be at least one standalone server, a distributed server, a cloud server, or a server cluster.

[0055] Furthermore, in this application, the scanning device and / or image reconstruction device in the magnetic resonance system stores a list of trusted devices. When the reconstruction resources of the magnetic resonance system itself cannot effectively handle multiple image reconstruction tasks to be performed, at least one trusted image reconstruction device can be selected from the list of trusted devices, and multiple image reconstruction tasks can be assigned to the trusted image reconstruction device for processing, so as to improve the image reconstruction efficiency of the magnetic resonance system.

[0056] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of this application. Those skilled in the art can make various changes and modifications to the image reconstruction system 100 based on the content of this application. Features, structures, methods, and other features of the exemplary embodiments described in this application can be combined in various ways to obtain other and / or alternative exemplary embodiments, and these changes and modifications will not depart from the scope of this application.

[0057] Next, the technical solutions of the embodiments of this application and how the technical solutions of the embodiments of this application solve the above-mentioned technical problems will be described in detail through specific examples and in conjunction with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. It should be noted that the image reconstruction method provided in the embodiments of this application can be executed by a scanning device or image reconstruction device within a magnetic resonance system, or it can be an image reconstruction apparatus. This apparatus can be implemented as part or all of a processor through software, hardware, or a combination of software and hardware. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments.

[0058] In one embodiment, such as Figure 2 As shown, an image reconstruction method is provided, which is applied to... Figure 1 The following steps are used as an example of the magnetic resonance system 110:

[0059] Step 210: In response to at least one image reconstruction task, determine the target device from the trusted device list of the magnetic resonance system; the trusted device list includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0060] The trusted device list includes multiple image reconstruction devices that the current magnetic resonance system can use for image reconstruction resources. Specifically, it may include device information such as device name, device identifier, hardware parameters, and the magnetic resonance system to which these image reconstruction devices belong, as well as the computing power level and priority of each image reconstruction device when processing image reconstruction tasks. The trusted device list can be stored in any device within the magnetic resonance system, such as scanning equipment, image reconstruction equipment, or other devices within the magnetic resonance system; this embodiment does not impose any restrictions on this.

[0061] It should be noted that the number of target devices can be determined based on at least one of the following: the number of image reconstruction tasks, the computing power requirement, and the processing speed. The number of target devices can be the same as or different from the number of image reconstruction tasks; this embodiment does not impose any restrictions on this.

[0062] In one possible implementation, step 210 can be implemented as follows: based on at least one reconstruction task generated in the magnetic resonance system, at least one image reconstruction device is selected as the target device from the multiple image reconstruction devices included in the trusted device list of the magnetic resonance system, and then the image reconstruction task is performed through the target device.

[0063] As an example, see the list of trusted devices shown in Table 1 below:

[0064] Table 1

[0065]

[0066]

[0067] As shown in Table 1, the magnetic resonance system A is internally equipped with two image reconstruction devices, A1 and A2, which can be used to process the image reconstruction tasks generated in the magnetic resonance system A. Furthermore, considering that the magnetic resonance system A may generate a large number of image reconstruction tasks, using image reconstruction devices A1 and A2 to process these tasks would result in slow processing speed and low imaging efficiency. Therefore, external image reconstruction devices C1 and C2, trusted by the magnetic resonance system A, are also added to the trusted device list of the magnetic resonance system A. In this way, the image reconstruction tasks generated in the magnetic resonance system A can be assigned to image reconstruction devices A1, A2, C1, and C2 for processing.

[0068] Similarly, for magnetic resonance system B, it is internally configured with an image reconstruction device B1. To improve image reconstruction speed without adding extra devices to the system, external image reconstruction devices C1 and C3, trusted by magnetic resonance system B, are also added to the trusted device list of magnetic resonance system B. In this way, image reconstruction tasks generated in magnetic resonance system B can be assigned to image reconstruction devices B1, C1, and C3 for processing.

[0069] It should also be noted that the trusted device list for the magnetic resonance system includes image reconstruction devices external to the magnetic resonance system, which may include separate computer equipment and / or image reconstruction devices within the magnetic resonance system. In other words, the trusted device list in this embodiment may include at least one image reconstruction device within the magnetic resonance system and an image reconstruction device external to the magnetic resonance system.

[0070] As another example, see the list of trusted devices shown in Table 2 below:

[0071] Table 2

[0072]

[0073]

[0074] As shown in Table 2, MRI systems A and B are mutually trusted systems, and their reconstruction resources can be shared. Therefore, the trusted device list of MRI system A includes not only its own image reconstruction devices A1 and A2, but also image reconstruction device B1 within MRI system B. Furthermore, the trusted device list of MRI system A also includes image reconstruction device C1 external to both MRI system A and MRI system B. In this way, image reconstruction tasks generated in MRI system A can be assigned to the four image reconstruction devices in the trusted list for execution, greatly improving the image reconstruction speed of MRI system A.

[0075] Similarly, the trusted device list of magnetic resonance system B includes not only its own image reconstruction device B1, but also the image reconstruction device A2 located within magnetic resonance system A. Furthermore, the trusted device list of magnetic resonance system B also includes image reconstruction devices C3 located outside of magnetic resonance system A and magnetic resonance system B. In this way, image reconstruction tasks generated in magnetic resonance system B can be assigned to the three image reconstruction devices in the trusted list for execution, significantly improving the image reconstruction speed of magnetic resonance system A.

[0076] Furthermore, if the shared reconstruction resources authorized by MRI system A to MRI system B also include image reconstruction device A1, then the trusted device list of MRI system B can also include: image reconstruction device A1 within MRI system A. In this way, the reconstruction resources between MRI system A and MRI system B are fully integrated and shared.

[0077] Step 220: Assign each image reconstruction task to the target device to instruct the target device to perform each image reconstruction task.

[0078] The number of image reconstruction tasks and the number of target devices can be the same, or the number of image reconstruction tasks can be greater than the number of target devices. This embodiment does not impose any restrictions on this.

[0079] If the number of image reconstruction tasks is the same as the number of target devices, then step 220 can be implemented as follows: assign the image reconstruction tasks to the corresponding image reconstruction devices, and each image reconstruction device performs one image reconstruction task.

[0080] If the number of image reconstruction tasks is greater than the number of target devices, then step 220 can be implemented as follows: based on the data processing volume of the image reconstruction tasks and the available computing resources of each image reconstruction device, the image reconstruction tasks are allocated to the target devices, and each target device executes at least one image reconstruction task.

[0081] In another possible implementation, the process of assigning the image reconstruction task to the target device can be as follows: a data transmission path is established between the magnetic resonance system and the target device. After the image reconstruction task is assigned, the image reconstruction task and related data are sent to the target device through the data transmission path, instructing the target device to perform the image reconstruction task according to the related data and generate the corresponding MRI image.

[0082] Furthermore, after completing the image reconstruction task, the target device can feed back the generated MRI images to the corresponding magnetic resonance system through a data transmission path.

[0083] Optionally, after creating a trusted device list for the MRI system, a data transmission path can be established between the MRI system and each image reconstruction device in the trusted list. After the image reconstruction task is assigned, the corresponding data transmission path is opened; after the MRI system receives the MRI image from the target device, the corresponding data transmission path is closed, and the resource sharing for this reconstruction ends.

[0084] In the aforementioned image reconstruction method, in response to at least one image reconstruction task, a target device is determined from a list of trusted devices within the magnetic resonance system (MRI) system. This list includes both internal and external image reconstruction devices. Each image reconstruction task is then assigned to the target device, instructing it to perform each task. In other words, this application integrates the reconstruction resources of both internal and external image reconstruction devices within the MRI system. Any trusted image reconstruction device can perform a portion of the MRI system's image reconstruction tasks. This breaks down the barriers to reconstruction resources between different MRI systems, allowing for resource sharing without requiring additional image reconstruction devices within the MRI system. This improves the image reconstruction speed and reduces the equipment investment cost. Furthermore, this method integrates the reconstruction resources of image reconstruction devices without adding extra equipment within the MRI system, thus preserving the original operating mechanism and principles of the MRI system and ensuring that the MRI imaging effect remains unaffected.

[0085] Following the above embodiments, in one embodiment, as Figure 3 As shown, step 210, which involves determining the target device from the trusted device list of the magnetic resonance system, specifically includes the following steps:

[0086] Step 310: Obtain the first candidate device that is on the same local area network as the magnetic resonance system.

[0087] It should be noted that, to ensure the data security of the magnetic resonance system, the target devices selected from the trusted device list should be located on the same local area network as the magnetic resonance system. Therefore, in response to at least one image reconstruction task generated by the magnetic resonance system, it is necessary to first obtain the image reconstruction devices included in the local area network where the magnetic resonance system is located, and use them as the first candidate devices.

[0088] In one possible implementation, step 310 can be implemented by: obtaining the operating status of the image reconstruction device that is on the same local area network as the magnetic resonance system; and identifying the image reconstruction device that is in an idle state as the first candidate device.

[0089] The operating status indicates whether the image reconstruction equipment is in an idle state. Each image reconstruction equipment can be set to reconstruction state when performing an image reconstruction task; when there are no image reconstruction tasks to be performed, the operating status can be set to idle state. Therefore, based on the operating status of each image reconstruction equipment, it can be determined whether its reconstruction resources can be utilized by the magnetic resonance system.

[0090] In practice, based on the local area network where the magnetic resonance system is located, multiple image reconstruction devices included in the local area network are obtained, and the operating status of multiple image reconstruction devices is viewed. The image device whose operating status is idle is determined as the first candidate device.

[0091] The number of first candidate devices is less than or equal to the number of image reconstruction devices in the local area network where the magnetic resonance system is located. For example, if the local area network where the magnetic resonance system is located includes ten image reconstruction devices, but as long as five image reconstruction devices are in an idle state, the final first candidate devices will be the five image reconstruction devices in an idle state.

[0092] Step 320: Based on the list of trusted devices, perform a trust check on the first candidate device to determine the target device.

[0093] The trust check is used to determine whether the first candidate device is a trusted device of the magnetic resonance system. When the first candidate device is a trusted device of the magnetic resonance system, it is identified as the target device.

[0094] It should be noted that the number of target devices is less than or equal to the number of image reconstruction tasks. That is, image reconstruction tasks are not split; one image reconstruction task can be assigned to one target device for processing, or multiple image reconstruction tasks can be assigned to one target device for processing.

[0095] In one possible implementation, the trusted device list also includes the priority of each image reconstruction device. Based on this, the implementation process of step 320 can be: determining a second candidate device belonging to the trusted device list from the first candidate device; and determining the target device from the second candidate device according to the priority of the second candidate device.

[0096] The priority of the second candidate device can be read from the list of trusted devices of the magnetic resonance system.

[0097] It is easy to understand that, in order to ensure data security, when there is no backlog of image reconstruction tasks inside the MRI system, the image reconstruction equipment inside the MRI system is used first to perform the image reconstruction tasks. There is no need to send the image reconstruction tasks and related data to the image reconstruction equipment outside the MRI system for processing, thereby reducing the risk of data leakage.

[0098] Therefore, the priority of multiple image reconstruction devices in the trusted device list is as follows: image reconstruction devices inside the MRI system have a higher priority than image reconstruction devices outside the MRI system. Furthermore, among the multiple image reconstruction devices outside the MRI system, their priority can be determined according to the reconstruction capabilities of each device.

[0099] As an example, the first candidate devices include: image reconstruction devices a, b, c, d, e, and f, while the trusted device list of the magnetic resonance system C includes: image reconstruction devices a, b, e, f, g, and h. Therefore, the second candidate devices selected from the first candidate devices are: image reconstruction devices a, b, e, and f.

[0100] If image reconstruction devices a and b are internal to the magnetic resonance system C, and image reconstruction devices e and f are external to the magnetic resonance system, and image reconstruction device e has a superior reconstruction capability compared to image reconstruction device f, then the priority of the aforementioned second candidate devices is as follows: image reconstruction devices a and b have the first priority, image reconstruction device e has the second priority, and image reconstruction device f has the third priority.

[0101] In cases where the priorities are the same, one of the multiple image reconstruction devices with that priority can be selected as the target device.

[0102] Following the previous example, based on the image reconstruction task, if three target devices are needed to complete the image reconstruction task, the determined target devices can be: image reconstruction device a, image reconstruction device b, and image reconstruction device e; if two target devices are needed to complete the image reconstruction task, the determined target devices can be: image reconstruction device a and image reconstruction device b. In this case, no external image reconstruction device is needed to provide reconstruction resources, and the image reconstruction device inside the magnetic resonance system C can complete the image reconstruction task; if only one target device is needed to complete the image reconstruction task, since image reconstruction device a and image reconstruction device b have the same priority, either image reconstruction device a or image reconstruction device b can be selected as the target device to perform the image reconstruction task.

[0103] In this embodiment, the target device is determined from the list of trusted devices based on multiple dimensions, including the local area network where the magnetic resonance system is located, the operating status of the image reconstruction equipment, trust checks, and the priority of the image reconstruction equipment. Thus, performing the image reconstruction task through the target device not only allows for efficient utilization of the image reconstruction equipment's reconstruction resources but also improves the image reconstruction speed of the magnetic resonance system.

[0104] Based on any of the above embodiments, in order to make full use of the reconstruction resources of the target device, when assigning image reconstruction tasks to the target device for processing, the target device corresponding to each image reconstruction task can be determined according to the computing power requirement value of the image reconstruction task and the computing power level of the target device, so as to ensure that the target device can successfully complete the corresponding image reconstruction task.

[0105] Based on this, in one embodiment, such as Figure 4 As shown, step 220 assigns each image reconstruction task to the target device, specifically including the following steps:

[0106] Step 410: Obtain the computing power requirements for each image reconstruction task and the computing power level of the target device.

[0107] The computational power requirement for an image reconstruction task can be determined based on the data processing volume and / or the estimated duration of the task. The computational power level of the target device can be a rating of its computing capabilities based on its hardware parameters (e.g., graphics card, memory, and available resources).

[0108] As an example, the computational power requirement for an image reconstruction task can be determined based on the amount of K-space data that needs to be processed. The larger the amount of K-space data to be processed, the greater the computational power requirement. Alternatively, the computational power requirement for an image reconstruction task can be determined based on the estimated computation time. The longer the estimated computation time, the greater the computational power requirement.

[0109] The computing power level of a target device can be automatically determined based on its hardware parameters; alternatively, the hardware parameters of the target device can be displayed, and users of the magnetic resonance system can rate each target device, with the user's rating result used as the target device's computing power level.

[0110] In one possible implementation, the computational power requirement for each image reconstruction task is calculated in real time, and the computational power level of the target device can be read from the list of trusted devices of the magnetic resonance system.

[0111] Step 420: Assign each image reconstruction task to the target device according to the computing power requirement and computing power level.

[0112] In other words, based on the computing power requirements of each image reconstruction task, it is allocated to target devices whose computing power level meets the requirements for processing. For target devices with higher computing power levels, multiple image reconstruction tasks can be assigned to them, while for target devices with lower computing power levels, only one image reconstruction task can be assigned to them.

[0113] Furthermore, after the image reconstruction task is assigned to the target device, the magnetic resonance system sends the relevant data for the corresponding image reconstruction task to the target device, which then performs the image reconstruction task.

[0114] In this embodiment, each image reconstruction task is assigned to the target device for processing based on the computing power requirements of each image reconstruction task and the computing power level of the target device. This ensures that the reconstruction resources of the target device are effectively utilized and that the target device can successfully complete the image reconstruction task. It also avoids situations where the image reconstruction task exceeds the computing power level of the target device, causing the target device to crash or malfunction while performing the image reconstruction task, thereby improving the image reconstruction speed of the magnetic resonance system.

[0115] Based on the above embodiments, for each magnetic resonance system, before executing the above image reconstruction method, it is necessary to first create a list of trusted devices to identify multiple image reconstruction devices that can share reconstruction resources.

[0116] Based on this, in one embodiment, such as Figure 5 As shown, this application also provides a method for creating a trusted device list for a magnetic resonance system, and this method is also applied to... Figure 1 The following steps are used as an example of the magnetic resonance system 110:

[0117] Step 510: Obtain the first device information of the image reconstruction device inside the magnetic resonance system, and the second device information of the image reconstruction device outside the magnetic resonance system.

[0118] The first piece of equipment information can be the configuration information of the image reconstruction equipment. For each MRI system, its internal image reconstruction equipment is assigned a unique equipment code at the factory, which corresponds one-to-one with each image reconstruction equipment in the MRI system. For each image reconstruction equipment within the MRI system, its built-in configuration information carries a system trust list, which includes the numbers of computer devices trusted by that image reconstruction equipment.

[0119] In other words, before each MRI system is put into use, the system can determine the computer equipment it trusts based on the configuration information of the image reconstruction equipment within the system. This computer equipment includes the image reconstruction equipment within the MRI system itself, as well as other trusted image reconstruction equipment within the MRI system.

[0120] Additionally, the image reconstruction equipment outside the MRI system may be a computer device used to perform other computational tasks, which can provide its own reconstruction resources to the MRI system when idle. Therefore, the second device information can be information that uniquely identifies a computer device, such as the computer device's Media Access Control Address (MAC) or device identifier.

[0121] Step 520: Create a list of trusted devices for the magnetic resonance system based on the first device information and the second device information.

[0122] In this step, the device codes of image reconstruction devices inside the magnetic resonance system are stored in the trusted device list, and the MAC addresses of image reconstruction devices outside the magnetic resonance system are stored in the trusted device list.

[0123] Optionally, the trusted device list may also include other information about the image reconstruction device, such as priority, computing power level, device identifier, hardware details, etc. This embodiment does not impose any restrictions on this.

[0124] In this embodiment, a trusted device list is pre-created for each magnetic resonance system based on the first device information of the image reconstruction equipment inside the magnetic resonance system and the second device information of the image reconstruction equipment outside the magnetic resonance system. Thus, when an image reconstruction task is generated, the magnetic resonance system can select a trusted image reconstruction task from the trusted device list to execute the task, thereby improving the image reconstruction speed of the magnetic resonance system without increasing the number of image reconstruction devices inside the system.

[0125] In one embodiment, such as Figure 6 As shown, this application also provides a method for updating a list of trusted devices, which is also applied to... Figure 1 The following steps are used as an example of the magnetic resonance system 110:

[0126] Step 610: Obtain device information for multiple image reconstruction devices that are on the same local area network as the magnetic resonance system.

[0127] The equipment information can be the equipment code of the image reconstruction equipment in the magnetic resonance system, or the MAC address of the image reconstruction equipment itself.

[0128] Optionally, the above step 610 can be executed periodically to obtain the device information of multiple image reconstruction devices, or the device information of multiple image reconstruction devices can be obtained in real time, or it can be obtained after the user triggers the update operation of the trusted device list of the magnetic resonance system. This embodiment does not limit this.

[0129] Step 620: Update the list of trusted devices for the magnetic resonance system based on the device information of each image reconstruction device.

[0130] In one possible implementation, step 620 can be implemented as follows: based on the device information of each image reconstruction device, deleting some existing image reconstruction devices from the trusted device list; and / or, adding new image reconstruction devices to the trusted device list; and / or, modifying and updating the device information of each image reconstruction device in the trusted devices.

[0131] In this embodiment, the trusted device list of the magnetic resonance system is updated based on the device information of the image reconstruction devices in the local area network where the magnetic resonance system is located, so as to ensure the validity of the trusted device list and thus ensure that the image reconstruction devices selected from the trusted device list can successfully perform the corresponding image reconstruction tasks.

[0132] In addition to the above embodiments, in one embodiment, this application also provides another image reconstruction method, which is also applied to... Figure 1 The following steps are used as an example of the magnetic resonance system 110:

[0133] S1: Obtain first device information of the image reconstruction device inside the magnetic resonance system, and second device information of the image reconstruction device outside the magnetic resonance system.

[0134] S2: Based on the first device information and the second device information, create a list of trusted devices for the magnetic resonance system.

[0135] S3: In response to at least one image reconstruction task generated by the magnetic resonance system, obtain the operating status of the image reconstruction device located on the same local area network as the magnetic resonance system.

[0136] S4: Identify the image reconstruction device that is in an idle state as the first candidate device.

[0137] S5: Perform a trust check on the first candidate device and determine the second candidate device that belongs to the trusted device list from the first candidate device.

[0138] S6: Determine the target device from the second candidate devices based on their priority.

[0139] The target device is either an image reconstruction device inside the magnetic resonance system or includes both an image reconstruction device inside the magnetic resonance system and an image reconstruction device outside the magnetic resonance system.

[0140] S7: Obtain the computing power requirements for each image reconstruction task and the computing power level of the target device.

[0141] S8: Assign each image reconstruction task to the target device based on the computing power requirement and computing power level.

[0142] S9: Open the data transmission path between the magnetic resonance system and the target device, send each image reconstruction task and related data to the target device, and instruct the target device to perform the corresponding image reconstruction task.

[0143] S10: Receive the reconstruction results from the target device and generate the corresponding MRI images.

[0144] S11: Update the list of trusted devices for the magnetic resonance system.

[0145] The implementation principle and technical effect of each step in the image reconstruction method provided in this embodiment are similar to those in the previous method embodiments. For specific limitations and explanations, please refer to the previous method embodiments, which will not be repeated here.

[0146] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0147] Based on the same inventive concept, this application also provides an image reconstruction apparatus for implementing the image reconstruction method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more image reconstruction apparatus embodiments provided below can be found in the limitations of the image reconstruction method described above, and will not be repeated here.

[0148] In one embodiment, such as Figure 7 As shown, an image reconstruction apparatus is provided, which includes: an equipment selection module 710 and a task allocation module 720, wherein:

[0149] The device selection module 710 is configured to determine a target device from a list of trusted devices of the magnetic resonance system in response to at least one image reconstruction task; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0150] The task allocation module 720 is used to allocate each image reconstruction task to the target device, so as to instruct the target device to perform each image reconstruction task.

[0151] In one embodiment, the device selection module 710 includes:

[0152] The first acquisition unit is used to acquire the first candidate device that is on the same local area network as the magnetic resonance system.

[0153] The trust check unit is used to perform trust checks on the first candidate device based on the list of trusted devices to determine the target device.

[0154] In one embodiment, the first acquisition unit includes:

[0155] The acquisition subunit is used to acquire the operating status of the image reconstruction equipment located on the same local area network as the magnetic resonance system; the operating status is used to indicate whether the image reconstruction equipment is in an idle state.

[0156] The first determining subunit is used to determine the image reconstruction device whose running state is idle as the first candidate device.

[0157] In one embodiment, the trusted device list also includes the priority of each image reconstruction device;

[0158] Trust checking unit, including:

[0159] The second determining subunit is used to determine a second candidate device belonging to the trusted device list from the first candidate devices;

[0160] The third determining subunit is used to determine the target device from the second candidate devices according to the priority of the second candidate devices.

[0161] In one embodiment, the task allocation module 720 includes:

[0162] The second acquisition unit is used to acquire the computing power requirements of each image reconstruction task and the computing power level of the target device;

[0163] The allocation unit is used to allocate each image reconstruction task to the target device according to the computing power requirement and computing power level.

[0164] In one embodiment, the device 700 further includes:

[0165] The first information acquisition module is used to acquire first device information of the image reconstruction device inside the magnetic resonance system and second device information of the image reconstruction device outside the magnetic resonance system.

[0166] A module is created to generate a list of trusted devices for the magnetic resonance system based on the first device information and the second device information.

[0167] In one embodiment, the device 700 further includes:

[0168] The second information acquisition module is used to acquire device information of multiple image reconstruction devices that are located on the same local area network as the magnetic resonance system;

[0169] The update module is used to update the list of trusted devices for the magnetic resonance system based on the device information of each image reconstruction device.

[0170] Each module in the aforementioned image reconstruction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0171] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements an image reconstruction method. The display unit of the computer device can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0172] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0173] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0174] In response to at least one image reconstruction task, a target device is determined from a list of trusted devices of the magnetic resonance system; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0175] Each image reconstruction task is assigned to the target device to instruct the target device to perform each image reconstruction task.

[0176] The computer device provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0177] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0178] In response to at least one image reconstruction task, a target device is determined from a list of trusted devices of the magnetic resonance system; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0179] Each image reconstruction task is assigned to the target device to instruct the target device to perform each image reconstruction task.

[0180] The computer-readable storage medium provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0181] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0182] In response to at least one image reconstruction task, a target device is determined from a list of trusted devices of the magnetic resonance system; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system.

[0183] Each image reconstruction task is assigned to the target device to instruct the target device to perform each image reconstruction task.

[0184] The computer program product provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0185] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0186] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0187] 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 the invention patent. 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 protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An image reconstruction method, characterized in that, The method includes: In response to at least one image reconstruction task, a target device is determined from the trusted device list of the magnetic resonance system based on the local area network where the magnetic resonance system is located, the running status of each image reconstruction task, trust checks, and the priority of each image reconstruction task; the trusted device list includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system; the number of target devices is determined based on at least one of the following: the number of image reconstruction tasks, the computing power requirement, and the processing speed. If the number of image reconstruction tasks is greater than the number of target devices, the computing power requirement of each image reconstruction task is determined based on the data processing volume of each image reconstruction task; and the computing power level of each target device is determined based on the hardware parameters of each target device. Based on the computing power requirements and computing power levels of each image reconstruction task, each image reconstruction task is assigned to each target device to instruct each target device to perform at least one image reconstruction task.

2. The method according to claim 1, characterized in that, The step of determining the target device from the trusted device list of the magnetic resonance system includes: Obtain the first candidate device that is on the same local area network as the magnetic resonance system; Based on the list of trusted devices, a trust check is performed on the first candidate device to determine the target device.

3. The method according to claim 2, characterized in that, The step of acquiring the first candidate device that is on the same local area network as the magnetic resonance system includes: The operating status of an image reconstruction device located on the same local area network as the magnetic resonance system is obtained; the operating status is used to indicate whether the image reconstruction device is in an idle state. The image reconstruction device that is in an idle state is identified as the first candidate device.

4. The method according to claim 2, characterized in that, The trusted device list also includes the priority of each of the image reconstruction devices; The step of performing a trust check on the first candidate device based on the trusted device list to determine the target device includes: Determine a second candidate device belonging to the trusted device list from the first candidate device; The target device is determined from the second candidate devices based on the priority of the second candidate devices.

5. The method according to any one of claims 1 to 4, characterized in that, The list of trusted devices includes at least the device name, device identifier, hardware parameters, and the magnetic resonance system to which the image reconstruction device belongs.

6. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Obtain first device information of the image reconstruction device inside the magnetic resonance system, and second device information of the image reconstruction device outside the magnetic resonance system; Based on the first device information and the second device information, a list of trusted devices for the magnetic resonance system is created.

7. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Obtain device information for multiple image reconstruction devices located on the same local area network as the magnetic resonance system; The list of trusted devices for the magnetic resonance system is updated based on the device information of each of the image reconstruction devices.

8. An image reconstruction apparatus, characterized in that, The device includes: A device selection module is configured to, in response to at least one image reconstruction task, determine target devices from a list of trusted devices of the magnetic resonance system based on the local area network where the magnetic resonance system is located, the running status of each image reconstruction task, trust checks, and the priority of each image reconstruction task; the list of trusted devices includes image reconstruction devices inside the magnetic resonance system and image reconstruction devices outside the magnetic resonance system; the number of target devices is determined based on at least one of the following: the number of image reconstruction tasks, computing power requirements, and processing speed. The task allocation module is used to determine the computing power requirement of each image reconstruction task based on the data processing volume of each image reconstruction task if the number of image reconstruction tasks is greater than the number of target devices; and to determine the computing power level of each target device based on the hardware parameters of each target device. Based on the computing power requirements and computing power levels of each image reconstruction task, each image reconstruction task is assigned to each target device to instruct each target device to perform at least one image reconstruction task.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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