Intelligent scheduling method and device of CT device, server and storage medium

Abstract

Embodiments of the present application provide a kind of intelligent scheduling method, device, server and storage medium of CT equipment, involve computer technical field.In the case where CT equipment is in idle state, the current heat capacity of CT equipment is obtained;In the case where current heat capacity is in the preset high-efficiency heat dissipation interval, for each item to be examined in the waiting pool of CT equipment, according to the examination data corresponding to the current heat capacity and the item to be examined, the predicted heat capacity after the item to be examined is carried out under the current heat capacity is calculated;According to the predicted heat capacity corresponding to each item to be examined, the target item to be examined currently to be executed by CT equipment is determined, to avoid the sudden increase of heat load out of limit leading to overheating of CT equipment, and to fully utilize the high-efficiency heat dissipation window to improve the continuous operation capability of CT equipment, so as to improve the overall operation efficiency under the premise of guaranteeing the safety of the bulb.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to an intelligent scheduling method, apparatus, server, and storage medium for CT equipment. Background Technology

[0002] Computed tomography (CT) is an indispensable imaging tool in modern clinical diagnosis, widely used in key areas such as tumor screening, trauma assessment, vascular lesion identification, and postoperative follow-up. Its image quality and examination efficiency directly affect the timeliness and accuracy of diagnostic and treatment decisions. The core component of a CT scanner—the X-ray tube—is mainly used to generate X-rays by bombarding a target surface with high-energy electrons, a process often accompanied by significant heat release.

[0003] With the popularization of multi-slice spiral CT technology, the proportion of complex examinations such as enhanced scanning and perfusion imaging continues to rise. These examinations are generally characterized by long exposure time, high tube current and tube voltage settings, and multiple sequential scanning. The heat load generated per unit time is much higher than that of conventional plain scanning, which keeps the X-ray tube in a state of high thermal stress for a long time.

[0004] Currently, radiology departments generally use a first-come, first-served scheduling logic, which arranges examinations according to the order of patient appointments or arrivals, focusing only on the temporal relationship of the task queue. While this model is simple and easy to implement from a management perspective, it can easily lead to heat buildup that exceeds the heat capacity limit of the X-ray tube, causing the CT equipment to trigger overheat protection and resulting in unplanned downtime of 15 to 20 minutes. Such interruptions disrupt the rhythm of all subsequent examinations, exacerbate waiting pressure, and, due to repeated exposure to extreme thermal cycles, accelerate the formation of cracks on the CT tube's anode target surface, leading to a shortened tube lifespan. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide an intelligent scheduling method, device, server and storage medium for CT equipment, so as to dynamically schedule the examination items according to the actual heat capacity, prevent the CT equipment from overheating, and improve the equipment protection effect and examination efficiency.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, this application provides an intelligent scheduling method for CT equipment, applied to a server, the server being communicatively connected to at least one CT equipment, the method comprising: When the CT device is in an idle state, obtain the current thermal capacity of the CT device; When the current heat capacity is within a preset high-efficiency heat dissipation range, for each item to be examined in the waiting pool of the CT equipment, the predicted heat capacity after performing the item to be examined is calculated based on the current heat capacity and the examination data corresponding to the item to be examined. Based on the predicted heat capacity corresponding to each of the items to be inspected, the target items to be inspected by the CT equipment are determined.

[0007] In an optional implementation, the examination data includes the heat load and equipment occupancy time corresponding to the items to be examined; the step of calculating the predicted heat capacity after performing the examination under the current heat capacity for each item to be examined in the waiting pool of the CT equipment, based on the current heat capacity and the examination data corresponding to the items to be examined, includes: For each examination item in the waiting pool of the CT equipment, the predicted heat capacity is calculated using the following formula:

[0008] in, For the current heat capacity, The equipment occupancy time corresponding to the item to be inspected. The cooling coefficient of the X-ray tube corresponding to the CT equipment. The heat load corresponding to the item to be inspected.

[0009] In an optional implementation, determining the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each of the inspection items includes: Based on the predicted heat capacity corresponding to each of the items to be inspected, candidate items to be inspected whose predicted heat capacity is less than the preset warning heat capacity are determined from a plurality of items to be inspected; If the candidate items to be inspected are not empty, then the candidate item to be inspected with the shortest device occupancy time is determined as the target item to be inspected; If the candidate items to be inspected are empty, then the minimum cooling time corresponding to the CT equipment is calculated based on the lowest heat load, the current heat capacity, and the warning heat capacity in the items to be inspected. After the CT equipment has waited for the minimum cooling time, the item to be inspected corresponding to the minimum heat load is determined as the target item to be inspected.

[0010] In an optional implementation, calculating the minimum cooling time corresponding to the CT equipment based on the lowest heat load in the item to be inspected, the current heat capacity, and the warning heat capacity includes: The minimum cooling time for the CT device is calculated using the following formula:

[0011] in, The minimum cooling time is given by k, where k is the cooling coefficient of the X-ray tube corresponding to the CT equipment. For the aforementioned warning heat capacity, For the minimum heat load, This refers to the current heat capacity.

[0012] In an optional implementation, the method further includes: When the current heat capacity is in the preset low heat range, the item with the highest heat load and the longest equipment occupation time among all the items to be inspected is determined as the target item to be inspected by the CT equipment at present. If the current heat capacity is within a preset warning range, the CT device will be controlled to stop working until the current heat capacity reaches the high-efficiency heat dissipation range. When the current heat capacity is within a preset shutdown range, the CT equipment is controlled to shut down.

[0013] In an optional implementation, the low-heat zone is less than the low-temperature heat capacity, the high-efficiency heat dissipation zone is greater than or equal to the low-temperature heat capacity and less than the warning heat capacity, the warning zone is greater than or equal to the warning heat capacity and less than the shutdown heat capacity, and the shutdown zone is greater than or equal to the shutdown heat capacity.

[0014] Secondly, this application provides an intelligent scheduling device for CT equipment, applied to a server, the server being communicatively connected to at least one CT device, the device comprising: The acquisition module is used to acquire the current thermal capacity of the CT device when the CT device is in an idle state. The calculation module is used to calculate the predicted heat capacity after performing the examination under the current heat capacity, based on the current heat capacity and the examination data corresponding to the examination items in the waiting pool of the CT equipment, when the current heat capacity is within a preset high-efficiency heat dissipation range. The determination module is used to determine the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each of the inspection items.

[0015] In an optional implementation, the examination data includes the heat load and equipment occupancy time corresponding to the items to be examined. The calculation module is further used to calculate the predicted heat capacity for each item to be examined in the waiting pool of the CT equipment using the following formula:

[0016] in, For the current heat capacity, The equipment occupancy time corresponding to the item to be inspected. The cooling coefficient of the X-ray tube corresponding to the CT equipment. The heat load corresponding to the item to be inspected.

[0017] Thirdly, this application provides a server including a processor and a memory, the memory storing a computer program executable by the processor, the processor being able to execute the computer program to implement the method described in any of the foregoing embodiments.

[0018] Fourthly, this application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the foregoing embodiments.

[0019] The intelligent scheduling method, apparatus, server, and storage medium for CT equipment provided in this application embodiment allow the server to acquire the current heat capacity of the CT equipment in real time when it is idle. If the current heat capacity is within a preset high-efficiency heat dissipation range, the server calculates the predicted heat capacity of each examination item in the waiting pool based on its corresponding examination data, under the current heat capacity. Subsequently, the server selects and determines the most suitable target examination item based on the current heat capacity and the predicted heat capacity corresponding to each examination item. Therefore, this method does not arrange examinations in a fixed order, but rather predicts the heat capacity based on the real-time thermal state of the equipment. It then makes dynamic scheduling decisions based on the prediction results and the current heat capacity, avoiding sudden increases in heat load that could lead to overheating of the CT equipment, while fully utilizing the high-efficiency heat dissipation window to improve the continuous operation capability of the CT equipment. This improves overall operating efficiency while ensuring the safety of the X-ray tube.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A block diagram of an intelligent scheduling system is shown. Figure 2A block diagram of a server provided in an embodiment of this application is shown; Figure 3 This invention illustrates a flowchart of an intelligent scheduling method for CT equipment provided in an embodiment of the present application. Figure 4 A schematic diagram showing the heat dissipation efficiency of different devices is provided. Figure 5 A schematic diagram showing the change in the heat capacity of the X-ray tube of CT device B during the simulation process is shown. Figure 6 A schematic diagram showing the change in the heat capacity of the X-ray tube of CT device I during the simulation process is shown; Figure 7 This diagram illustrates the test results of the production capacity of each CT device during the simulation process. Figure 8 This paper illustrates a functional block diagram of an intelligent scheduling device for a CT scanner provided in an embodiment of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0025] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0026] Figure 1This is a block diagram of an intelligent scheduling system, which includes a server and at least one CT device, and the server is communicatively connected to the CT device.

[0027] exist Figure 1 On this basis, Figure 2 Please refer to the block diagram of the server provided in the embodiments of this application. Figure 2 The server includes a memory, a processor, and a communication module. These components are electrically connected directly or indirectly to enable data transmission or interaction. For example, they can be electrically connected via one or more communication buses or signal lines.

[0028] Memory is used to store computer programs or data that can be executed by a processor. Memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc.

[0029] The processor is used to read / write data or computer programs stored in the memory and execute the computer program to implement the intelligent scheduling method for CT equipment provided in the embodiments of this application.

[0030] The communication module is used to establish communication connections between the server and other communication terminals via the network, and to send and receive data via the network.

[0031] It should be understood that, Figure 2 The structure shown is only a schematic diagram of the server structure; the server may also include components such as... Figure 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown. Figure 2 The components shown can be implemented using hardware, software, or a combination thereof.

[0032] The following is based on the above. Figure 1 The server in this application serves as the execution entity. The intelligent scheduling method for CT equipment provided in this embodiment is described executively with reference to the flowchart.

[0033] Specifically, Figure 3Please refer to the flowchart of the intelligent scheduling method for CT equipment provided in the embodiments of this application. Figure 3 The method includes: Step S20: When the CT equipment is in an idle state, obtain the current thermal capacity of the CT equipment.

[0034] In this embodiment, the idle state refers to the time period when the current inspection has been completely completed, the X-ray tube has stopped exposure, and the equipment has not started the next inspection (i.e., the tasks to be performed in the waiting pool have not yet been scheduled and started).

[0035] The server can obtain the current thermal capacity of the CT device through the built-in sensors of the CT device when the CT device is in an idle state, or determine the current thermal capacity of the CT device based on the real-time operating data reported by the CT device.

[0036] Step S21: When the current heat capacity is within the preset high-efficiency heat dissipation range, for each examination item in the waiting pool of the CT equipment, calculate the predicted heat capacity after the examination item is performed under the current heat capacity, based on the current heat capacity and the examination data corresponding to the examination item.

[0037] In this embodiment, the high-efficiency heat dissipation range refers to the heat capacity range under conditions where the temperature difference between the X-ray tube of the CT equipment and the environment is large and the natural heat dissipation rate is high. It belongs to the temperature window that is most conducive to continuous operation in terms of the physical characteristics of the equipment.

[0038] Optionally, the high-efficiency heat dissipation zone can be determined in advance according to the characteristics of the CT equipment, for example, set to 50% to 85% of the maximum heat capacity.

[0039] Optionally, each CT scanner has a corresponding waiting pool, which includes at least one examination to be performed next. Furthermore, the examination data for different examinations can be pre-obtained based on real clinical data.

[0040] Step S22: Determine the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each inspection item.

[0041] Optionally, to prevent the CT equipment from overheating and causing shutdown, a heat capacity threshold slightly smaller than the shutdown heat capacity can be set to rigidly constrain the next examination task that can be executed normally under the current heat capacity. This determines the feasible domain of tasks that the CT equipment can execute normally without triggering overheating shutdown, and thus determines the next target examination item to be executed.

[0042] In this embodiment, the server can schedule the target items to be examined after determining them, so as to perform the corresponding examinations on the corresponding patients.

[0043] The intelligent scheduling method for CT equipment provided in this application involves the server acquiring the current heat capacity of the CT equipment in real time when it is idle. If the current heat capacity is within a preset high-efficiency heat dissipation range, the server calculates the predicted heat capacity of each examination item in the waiting pool, based on its corresponding examination data, under the current heat capacity. Subsequently, the server selects and determines the most suitable target examination item based on the current heat capacity and the predicted heat capacity corresponding to each examination item. Therefore, this method does not arrange examinations in a fixed order, but rather predicts the heat capacity based on the real-time thermal state of the equipment. It then makes dynamic scheduling decisions based on the prediction results and the current heat capacity, avoiding sudden increases in heat load that could lead to overheating of the CT equipment, while fully utilizing the high-efficiency heat dissipation window to improve the continuous operation capability of the CT equipment. This improves overall operating efficiency while ensuring the safety of the X-ray tube.

[0044] The following provides a possible implementation method for calculating the predicted heat capacity after performing the examination under the current heat capacity, based on the current heat capacity and the corresponding examination data for each examination item in the waiting pool of the CT equipment.

[0045] In this embodiment, the inspection data includes the heat load H and equipment occupancy time T corresponding to the item to be inspected. In addition, the inspection data may also include the inspection type. That is, for an inspection item, its inspection data can be defined as a tuple E, and .

[0046] In this embodiment, heat load refers to the quantitative value of the increase in heat capacity of the X-ray tube caused by performing one examination, and equipment occupancy time refers to the total time taken for the examination from when the patient enters the examination room, completes the positioning, exposure scanning, to when the patient leaves the room.

[0047] In one possible implementation, the aforementioned data can be obtained in advance through data analysis and statistics based on real CT equipment log data generated during actual hospital operations. This log data covers 10 CT machines of the same brand deployed in the hospital, each connected to the hospital's medical equipment IoT platform, and continuously collecting complete work logs for more than a month. These log records cover multiple clinical business scenarios such as emergency department, physical examination center, outpatient department, and inpatient department, thus comprehensively reflecting the differentiated usage pressure of CT equipment in the daily operation of departments with different functional positions. The raw data fields may include the unique identifier of the equipment, the start and end timestamps of the examination event, the name of the examination item, the heat capacity value of the X-ray tube at the start of the examination, and the corresponding heat capacity value at the end of the examination. All data has been anonymized and does not contain any information that can identify the patient.

[0048] In the early stages of data analysis, log data can be preprocessed. For example, based on the standard field dictionary provided by the equipment manufacturer, log entries generated by non-diagnostic operating states such as warm-up, idling, and self-test can be removed first, and only valid records with clear clinical examination intent and complete process can be retained. Finally, multiple examination instances that can be used for modeling and verification can be selected (55,405 cases in this example).

[0049] Subsequently, all examination items were categorized into ten typical types based on clinical significance, including enhanced abdominal scan, combined chest and abdominal scan, various CTA scans, plain abdominal scan, plain head scan, limb scan, enhanced / perfusion head scan, plain neck scan, spine scan, and plain chest scan. See Table 1 below for details.

[0050] Table 1

[0051] It should be noted that the average examination time in Table 1 refers to the average exposure time of the CT equipment. Each examination requires multiple exposure events to obtain the final examination result. Therefore, the average examination time needs to be calculated in combination with the total exposure time corresponding to multiple exposure events.

[0052] Each of the above examinations is assigned three core quantitative attributes: the first is the heat load (average heat capacity in Table 1), which is the absolute amount of increase in heat capacity of the X-ray tube caused by a single examination, in units of heat capacity (HU). This value is directly measured by the built-in sensor of the equipment and output after calibration; the second is the equipment occupancy time, which refers to the total time taken from when the patient enters the examination room, completes the positioning, starts the scan, to when the patient leaves the examination room, rather than just the exposure time. This indicator comprehensively reflects the actual degree of equipment resource occupation in the actual workflow of the examination; the third is the examination type identifier, which is used to distinguish the physical and operational characteristics corresponding to different anatomical sites, scanning methods, and imaging requirements.

[0053] Based on this, all examinations can be further divided into two categories: high heat load type and low heat load type. The former is represented by abdominal enhanced scan, which is characterized by high heat load and long equipment occupation time. The latter is represented by chest plain scan, which is characterized by low heat load and short operation process. It is particularly suitable as a buffer task in the process of heat capacity regulation. It can be performed intermittently when the tube temperature is close to the safe threshold to achieve dynamic balance of cold and heat.

[0054] Optionally, the server can update the device usage time periodically, such as weekly or monthly, based on newly added log data during that period. Understandably, this device usage time is obtained through statistics from the hospital's massive log data, inevitably covering multiple CT scanners and various application scenarios in different departments (including emergency, outpatient, health check-up center, and inpatient ward). Therefore, it can objectively reflect the typical operating rhythm of various examination types and has universal applicability.

[0055] In one possible approach, the occupancy time of CT equipment in each department can be statistically analyzed to match the examination schedule of the specific department.

[0056] In order to accurately predict the thermal capacity state of the CT equipment after performing the examination, a thermodynamic model of the CT tube corresponding to the CT equipment can be constructed in advance.

[0057] Specifically, the thermodynamic model is constructed based on the actual heat accumulation and dissipation of the X-ray tube during actual operation. The core objective is to achieve high-precision dynamic prediction of the heat capacity state of the X-ray tube, characterized as follows:

[0058] in, for Predicted heat capacity after duration Let be the heat capacity of the CT tube at time t. The duration of the check after time t. The heat load generated during the j-th inspection, for All examinations performed by the CT scanner during this period The cooling coefficient of the X-ray tube can be calculated in advance based on the log data of the CT equipment through regression fitting analysis.

[0059] In one possible implementation, the server can calculate the heat difference between two adjacent CT scans based on the heat generated after each scan and the heat generated before the next scan. This heat difference characterizes the heat dissipation of the X-ray tube during the cooling period. Then, based on multiple heat differences, the X-ray tube cooling coefficient is obtained by fitting the data using the following formula. :

[0060] in, For the calorie difference, This refers to the cooling time between two consecutive checks.

[0061] It should be noted that in the above thermodynamic model of the CT tube, the temperature decay process of the tube under no-load conditions is modeled as an exponential decay, and its decay rate can be determined by the inherent cooling coefficient of the tube. This coefficient can reflect the individual heat dissipation capabilities of different CT devices due to differences in service life, ambient temperature and humidity, and the degree of aging of the heat dissipation structure. In one possible implementation, the measured range of this tube cooling coefficient is between 0.012 and 0.043 per minute.

[0062] When an examination is being performed, the heat capacity of the X-ray tube is not only affected by its own cooling, but also by the heat load generated by the current examination—this gain can be determined based on the specific examination type. Therefore, in this embodiment, the server can calculate the predicted heat capacity for each examination item in the CT equipment's waiting pool using the following formula:

[0063] in, Given the current heat capacity, The duration of equipment usage for the items to be inspected. The coefficient of performance (COP) for the X-ray tube of the CT equipment. This represents the heat load corresponding to the items to be inspected.

[0064] Understandably, in practical applications, the server can predict the heat capacity that the CT equipment may reach after performing the corresponding inspection task, based on the heat load corresponding to the inspection task, the inspection data of the inspection task, and the aforementioned thermodynamic model. .

[0065] Next, the server can determine the target inspection item to be performed by the CT equipment based on the current heat capacity and the predicted heat capacity corresponding to each inspection item.

[0066] In this embodiment, the server can first determine candidate items whose predicted heat capacity is less than the preset warning heat capacity from multiple items to be inspected based on the predicted heat capacity corresponding to each item to be inspected.

[0067] If the candidate items to be inspected are not empty, the candidate item to be inspected with the shortest equipment occupancy time is determined as the target item to be inspected; if the candidate items to be inspected are empty, the minimum cooling time corresponding to the CT equipment is calculated based on the minimum heat load, current heat capacity and warning heat capacity in the items to be inspected, and after the CT equipment waits for the minimum cooling time, the item to be inspected corresponding to the minimum heat load is determined as the target item to be inspected.

[0068] In this embodiment, the server can dynamically select feasible inspection tasks that will not cause the X-ray tube heat capacity to exceed the warning threshold based on the current heat capacity and inspection data of various items to be inspected when the CT equipment is in the high-efficiency heat dissipation range. When feasible tasks exist, the task with the shortest time is given priority. When no feasible tasks exist, a precisely calculated cooling waiting time is actively inserted before executing the task with the least heat generation, thereby achieving forward-looking and non-linear control of the X-ray tube thermal state.

[0069] It should be understood that CT tubes are not necessarily better off when they are as cold as possible—their heat dissipation efficiency follows Newton's law of cooling, depending on the temperature difference between the tube and the environment. When the tube temperature is too low, the temperature difference with the environment is small, and heat dissipation is slow, which is actually detrimental to timely heat dissipation. On the other hand, when the temperature approaches the dangerous level of the warning heat capacity, although the temperature difference with the environment is large and heat dissipation is fast, continuing to scan can easily trigger the shutdown threshold, leading to overheating and forced interruption. Therefore, simply pursuing "no shutdown" or "no waiting" is not feasible. The key is to keep the tube temperature stable within the efficient heat dissipation range—a safe window with a moderate temperature difference and efficient heat dissipation.

[0070] Based on this, a heat capacity threshold slightly lower than the shutdown heat capacity can be introduced, i.e., a warning heat capacity, so that the intervention mechanism can be activated before the heat capacity actually reaches the danger threshold. This leads to two heat capacity constraints with different functional orientations: shutdown heat capacity and shutdown heat capacity. and early warning heat capacity .

[0071] Among them, shutdown heat capacity The maximum heat capacity of the CT scanner can be set to 95%, representing a rigid boundary for the physical safety of the X-ray tube. Exceeding this value requires the scanner to immediately stop scanning and begin cooling. Its purpose is to prevent thermal overload damage to the hardware. The warning heat capacity... It can be set to 85% of the maximum heat capacity. It does not directly trigger a shutdown, but serves as a decision trigger point for the intelligent scheduling strategy. When the predicted heat capacity approaches or reaches this value, the server will proactively adjust the subsequent inspection schedule, such as prioritizing the insertion of low heat load tasks or initiating a short wait, thereby keeping the thermal state stably constrained within the efficient heat dissipation range and preventing it from sliding to the edge of danger.

[0072] Based on this, the above problem can be defined as the following two objective functions, where the constraint on shutdown can be characterized as: The constraints on early warning can be characterized as follows: .

[0073] in, Indicates an indicator function, Indicates the first The significance of the shutdown constraint mentioned above is that the CT tube must be shut down for cooling when it reaches 95% of its maximum heat capacity. The purpose of the early warning constraint is to constrain the heat capacity indicators that need to be warned in intelligent scheduling. It can be understood that the shutdown constraint constitutes an insurmountable hard limit, while the early warning constraint is an adjustment lever to pursue better operating quality under the premise of meeting the hard limit.

[0074] In this embodiment, at any decision-making moment, the server can first determine the current heat capacity of the X-ray tube. Based on the heat load and equipment occupancy time corresponding to each examination item in the waiting pool, calculate the predicted heat capacity after the examination is performed; then, based on... All candidate items to be inspected that are still below the warning threshold based on predicted heat capacity are selected. These candidate items can constitute the currently executable task feasible domain. .

[0075] If the feasible domain of the task is not empty, the task to be inspected with the shortest equipment occupancy time can be selected as the target task to be inspected, and low heat load tasks should be prioritized for scheduling.

[0076] If the feasible domain of this task is empty, it means that executing any of the examination items in the waiting pool individually would cause the X-ray tube heat capacity to reach or exceed the warning heat capacity. At this time, the server does not force any scans, but instead initiates an active waiting mechanism. That is, based on the lowest heat load, current heat capacity, and warning heat capacity of the items to be inspected, it calculates the minimum cooling time corresponding to the CT equipment. After the CT equipment waits for this time, the item with the lowest heat load is then executed.

[0077] In one possible implementation, the server can calculate the minimum cooling time for the CT device using the following formula:

[0078] in, The minimum cooling time is given by k, where k is the cooling coefficient of the X-ray tube corresponding to the CT equipment. To provide early warning of heat capacity, For minimum heat load, This represents the current heat capacity.

[0079] It should be noted that although the above scheduling method usually does not result in the heat capacity exceeding the warning heat capacity, in actual application, there may be emergencies such as emergency patients jumping the queue, priority patients jumping the queue, causing the actual heat capacity after the examination to exceed the warning heat capacity, or patients not cooperating, causing changes in equipment usage time, resulting in fluctuations in the prediction and a mismatch between the actual heat capacity after the examination and the prediction. Therefore, the server can also dynamically adjust the scheduling priority of the examination items based on the specific temperature range of the CT equipment's actual current heat capacity, so as to actively intervene in the heat status of the X-ray tube and maximize the continuous examination capacity and service life of the CT equipment.

[0080] Specifically, the server can also identify the item with the highest heat load and longest equipment usage time among all items to be inspected as the target item to be inspected by the CT equipment when the current heat capacity is in the preset low heat range; when the current heat capacity is in the preset warning range, control the CT equipment to stop working until the current heat capacity reaches the efficient heat dissipation range; and when the current heat capacity is in the preset shutdown range, control the CT equipment to shut down.

[0081] In this embodiment, the low-heat range is less than the low-temperature heat capacity, the high-efficiency heat dissipation range is greater than or equal to the low-temperature heat capacity and less than the warning heat capacity, the warning range is greater than or equal to the warning heat capacity and less than the shutdown heat capacity, and the shutdown range is greater than or equal to the shutdown heat capacity.

[0082] In this embodiment, the current heat capacity of the X-ray tube can be divided into four intervals based on three preset values: low-heat interval, high-efficiency heat dissipation interval, warning interval, and shutdown interval. The low-temperature heat capacity refers to a preset baseline threshold, corresponding to the minimum heat capacity level required for the X-ray tube to enter a high-efficiency heat dissipation state; in one possible implementation, this low-temperature heat capacity can be 50% of the maximum heat capacity. The warning heat capacity refers to the heat capacity threshold for initiating soft intervention measures; in one possible implementation, this low-temperature heat capacity can be 85% of the maximum heat capacity. The shutdown heat capacity refers to the hard upper limit for triggering mandatory protective shutdown; in one possible implementation, this low-temperature heat capacity can be 95% of the maximum heat capacity. All the above interval divisions are calibrated based on the actual heat dissipation characteristics of the CT equipment and obtained through large-scale clinical log regression analysis.

[0083] It should be understood that the heat dissipation capacity of a CT tube varies significantly at different temperatures: according to Newton's law of cooling, its heat dissipation rate is directly proportional to the temperature difference between the tube and the environment; when the tube temperature is too low, the temperature difference is small and the heat dissipation is slow, and the equipment being in a low-temperature zone for a long time will reduce the thermal management efficiency per unit time; while when the tube temperature is moderate (i.e., there is a large temperature difference with the environment), the heat dissipation rate is high, which is conducive to maintaining thermal balance during continuous operation; but if the temperature is too high, there is a risk of overheating and shutdown.

[0084] Based on this, this embodiment can implement a differentiated scheduling strategy based on the current heat capacity range of the CT equipment. Specifically, when the current heat capacity is less than the low-temperature heat capacity, the equipment is in the low-temperature zone. At this time, the temperature difference is small and the heat dissipation efficiency is low. Therefore, the examination item with the highest heat load and the longest equipment occupation time among all examination items can be identified as the target examination item to be executed. High-heat composite tasks are given priority to quickly increase the X-ray tube temperature. On the one hand, this avoids the continuous accumulation of high-heat load tasks in the waiting pool, and on the other hand, it prompts the X-ray tube to enter the high-efficiency working range with a larger temperature difference and faster heat dissipation as soon as possible.

[0085] When the current heat capacity is greater than or equal to the low-temperature heat capacity and less than the warning heat capacity, the CT equipment is in the high-efficiency heat dissipation range. At this time, the temperature difference is large and the heat dissipation rate is high. Therefore, the target inspection item to be performed by the CT equipment can be determined based on the current heat capacity and the predicted heat capacity corresponding to each inspection item through the above method. The high heat dissipation rate can be used to suppress the heat capacity from rising further, thereby extending the continuous operation window of the equipment without shutdown.

[0086] When the current heat capacity is greater than or equal to the warning heat capacity but less than the shutdown heat capacity, the equipment has entered the warning zone. Although the forced shutdown threshold has not yet been reached, continuing to perform any inspection may trigger the shutdown heat capacity red line. Therefore, the CT equipment needs to be stopped and allowed to cool naturally until the current heat capacity drops back to the efficient heat dissipation zone before resuming operation. During this phase, no inspections are performed; the equipment simply waits passively to ensure a safety margin.

[0087] It should be noted that once the current heat capacity drops to the efficient heat dissipation range, the server can continue to calculate the predicted heat capacity after performing the examinations for each item in the CT equipment's waiting pool, based on the current heat capacity and the examination data corresponding to the items. Then, based on the predicted heat capacity corresponding to each item, the server can determine the target examination item to be performed by the CT equipment.

[0088] When the current heat capacity is greater than or equal to the shutdown heat capacity, the equipment has entered the shutdown zone and triggered overheat protection. At this time, the server needs to immediately control the CT equipment to shut down and start the forced cooling process.

[0089] Next, using physical simulations closely resembling clinical practice, we will further explain the implementation effect of the intelligent scheduling method for CT equipment provided in this application embodiment. Specifically, firstly, based on the complete examination logs (55,405 cases) of 10 CT machines of the same brand for a continuous month, we can perform probabilistic modeling of the examination type composition for each machine, statistically derive the distribution pattern of high-frequency examination items for each machine, and construct a clinically representative waiting pool state for each CT machine accordingly. This distribution not only reflects the proportion of each examination type but also reflects the structural differences between different machines. In one example, Figure 4 For a diagram illustrating the heat dissipation efficiency of different devices, please refer to [link / reference]. Figure 4 As can be seen, even CT scanners of the same brand can have different X-ray tube cooling coefficients due to factors such as the environment in which the equipment is used, its age, and its specific heat dissipation design. This X-ray tube cooling coefficient characterizes the heat dissipation efficiency of the CT scanner and is positively correlated with it. Furthermore, the distribution of examination volumes for different equipment is shown in Table 2. Table 2

[0090] Please refer to Table 2. This embodiment summarizes the three most commonly used examinations for each CT device. Among them, chest and abdominal plain scans are the most important examination items for all devices.

[0091] During the simulation, after each check is completed, the server randomly generates new tasks to be checked based on the probability distribution of the device's historical checks and places them in the waiting pool, thus simulating the volatility and heterogeneity of real outpatient traffic. To enhance the statistical reliability of the results, each device runs continuously for 12 hours under full load and repeats 10 rounds of independent simulation, with the average value of each indicator ultimately used as the evaluation criterion.

[0092] Figure 5 This is a schematic diagram illustrating the change in the heat capacity of the X-ray tube of CT device B during the simulation process. Figure 6 For a schematic diagram illustrating the change in the X-ray tube heat capacity of CT device I during the simulation process, please refer to [link / reference]. Figures 5-6 The inspection distribution of equipment B is similar to that of equipment I, but the tube cooling coefficient of equipment B is different. Since device B is larger than device I, its heat capacity remains stable around 50% with slight fluctuations under both the random scheduling mode in the prior art and the intelligent scheduling mode in this application, reflecting that the system's heat dissipation capacity and heat generation rhythm are basically matched and the thermal balance is good. Device I is different. If the random scheduling method in the prior art is used, its heat capacity curve will frequently approach or even exceed the 95% forced fuse threshold, triggering protective shutdown and causing operation interruption. However, if the intelligent scheduling strategy in this application is adopted, its curve shows obvious active control characteristics - the heat capacity can be effectively constrained below the 85% safety warning line, the overall fluctuation is more gradual, and it is always in the optimal heat dissipation efficiency range of 50% to 85%, which avoids the risk of overheating and makes full use of the natural cooling advantage driven by temperature difference.

[0093] Furthermore, according to simulation results, for equipment with fewer high-heat-load tasks, both the intelligent scheduling method proposed in this application and the random arrangement method in the prior art can achieve good heat control, with the heat capacity of the X-ray tube fluctuating around 50%. However, for equipment with many high-heat-load tasks (such as equipment G), the random allocation method in the prior art cannot meet the heat control requirements. After overheating, the equipment must be shut down and allowed to cool down before inspection can continue. In contrast, the intelligent allocation method proposed in this application can first schedule high-heat-load tasks to raise the temperature of the equipment, keeping it at its highest heat dissipation efficiency, and then allocate appropriate inspections to maintain the change in the equipment's heat capacity.

[0094] Table 3 shows the number of times different equipment stopped due to 10 simulated 12-hour continuous pressure tests.

[0095] Table 3

[0096] also, Figure 7 Please refer to the schematic diagram of the capacity test results of each CT device during the simulation process. Figure 7As shown in Table 3 above, the simulation results reveal that under the random scheduling mode without any scheduling intervention, different devices exhibit significantly different thermal stability performance. Devices with lower heat dissipation efficiency and a higher proportion of high-heat-load inspections, such as devices G and D, triggered forced shutdowns an average of 11.1 and 10.0 times respectively during the 12-hour stress test, with the highest single shutdown reaching 12 times, causing a large number of inspections to be interrupted and transferred to the waiting queue. In contrast, after applying the intelligent scheduling strategy of this application, all 10 devices achieved zero downtime operation in all 10 rounds of simulation. In particular, device G, which was originally prone to overheating, not only never experienced overheating shutdowns but also achieved an 18% increase in inspection throughput. The other devices also showed varying degrees of capacity growth. This indicates that the intelligent scheduling strategy of this application not only avoids the risk of overheating shutdowns but also utilizes the time originally used for passive cooling to increase inspection capacity.

[0097] Based on the simulation results above, it can be concluded that the risk of thermal failure of CT tubes is not essentially determined by the total number of examinations, but rather highly dependent on the combination of examination types over time and their matching relationship with the inherent heat dissipation characteristics of the equipment. Traditional first-come, first-served random scheduling mechanisms ignore the time lag and nonlinearity of thermodynamic response, easily inducing localized accumulation of heat load and positive feedback deterioration. The intelligent scheduling strategy provided in this application, by integrating the principle of temperature difference-driven heat dissipation revealed by Newton's law of cooling, actively regulates the operating temperature range of the CT tube, maintaining it within the optimal heat dissipation efficiency "golden temperature zone" of 50% to 85% over the long term. Within this framework, a dynamic interleaving and proactive waiting mechanism for hot and cold tasks is implemented. Essentially, this achieves improved operational efficiency at a minimal time cost, unlocking up to 18% additional potential service capacity for hospitals. This provides a feasible technical path for large hospital radiology departments to achieve synergistic optimization of equipment health and service efficiency.

[0098] To perform the corresponding steps in the above embodiments and various possible methods, an implementation of an intelligent scheduling device for CT equipment is given below. Optionally, the intelligent scheduling device for CT equipment can adopt the above-described... Figure 2 The server's device structure is shown. For further details, please refer to... Figure 8 , Figure 8 This is a functional block diagram of an intelligent scheduling device for CT equipment provided in this application embodiment. It should be noted that the basic principle and technical effects of the intelligent scheduling device for CT equipment provided in this embodiment are the same as those in the above embodiments. For the sake of brevity, any parts not mentioned in this embodiment can be referred to the corresponding content in the above embodiments. The device includes: an acquisition module, a calculation module, and a determination module.

[0099] This acquisition module is used to acquire the current thermal capacity of the CT device when the CT device is idle.

[0100] Understandably, this acquisition module can also be used to perform the above step S20.

[0101] This calculation module is used to calculate the predicted heat capacity after performing the examinations in the waiting pool of the CT equipment, based on the current heat capacity and the examination data corresponding to the examinations, when the current heat capacity is within a preset high-efficiency heat dissipation range.

[0102] Understandably, this calculation module can also be used to perform the above step S21.

[0103] This determination module is used to determine the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each inspection item.

[0104] Understandably, this determining module can also be used to perform step S22 above.

[0105] Optionally, the inspection data includes the heat load and equipment occupancy time corresponding to the items to be inspected. The calculation module is also used to calculate the predicted heat capacity for each item to be inspected in the waiting pool of the CT equipment using the following formula: ;in, Given the current heat capacity, The duration of equipment usage for the items to be inspected. The coefficient of performance (COP) for the X-ray tube of the CT equipment. This represents the heat load corresponding to the items to be inspected.

[0106] Optionally, the determining module is further configured to determine, based on the predicted heat capacity corresponding to each item to be inspected, candidate items whose predicted heat capacity is less than a preset warning heat capacity from multiple items to be inspected; if the candidate items to be inspected are not empty, then the candidate item to be inspected with the shortest equipment occupancy time is determined as the target item to be inspected; if the candidate items to be inspected are empty, then the minimum cooling time corresponding to the CT equipment is calculated based on the minimum heat load, current heat capacity and warning heat capacity in the items to be inspected; after the CT equipment waits for the minimum cooling time, the item to be inspected corresponding to the minimum heat load is determined as the target item to be inspected.

[0107] Optionally, the determining module is also used to calculate the minimum cooling time corresponding to the CT device using the following formula: ;in, The minimum cooling time is given by k, where k is the cooling coefficient of the X-ray tube corresponding to the CT equipment. To provide early warning of heat capacity, For minimum heat load, This represents the current heat capacity.

[0108] Optionally, the determining module is further configured to: when the current heat capacity is in a preset low heat range, determine the inspection item with the highest heat load and the longest equipment occupation time among all inspection items as the target inspection item to be executed by the CT equipment; when the current heat capacity is in a preset warning range, control the CT equipment to stop working until the current heat capacity reaches the efficient heat dissipation range; and when the current heat capacity is in a preset shutdown range, control the CT equipment to shut down.

[0109] Optionally, the above modules can be stored in the form of software or firmware. Figure 2 The memory shown is either stored in or embedded in the server's operating system (OS), and can be used by... Figure 2 The processor executes the commands. Meanwhile, the data and program code required to execute these modules can be stored in memory.

[0110] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the intelligent scheduling method for CT equipment provided in this application.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0112] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0113] If a function is implemented as a software module and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An intelligent scheduling method for CT equipment, characterized in that, Applied to a server, the server being communicatively connected to at least one CT device, the method includes: When the CT device is in an idle state, obtain the current thermal capacity of the CT device; When the current heat capacity is within a preset high-efficiency heat dissipation range, for each item to be examined in the waiting pool of the CT equipment, the predicted heat capacity after performing the item to be examined is calculated based on the current heat capacity and the examination data corresponding to the item to be examined. Based on the predicted heat capacity corresponding to each of the items to be inspected, the target items to be inspected by the CT equipment are determined.

2. The method according to claim 1, characterized in that, The inspection data includes the heat load and equipment occupancy time corresponding to the items to be inspected; the calculation of the predicted heat capacity after performing the items to be inspected under the current heat capacity, based on the current heat capacity and the inspection data corresponding to the items to be inspected in the waiting pool of the CT equipment, includes: For each examination item in the waiting pool of the CT equipment, the predicted heat capacity is calculated using the following formula: in, For the current heat capacity, The equipment occupancy time corresponding to the item to be inspected. The cooling coefficient of the X-ray tube corresponding to the CT equipment. The heat load corresponding to the item to be inspected.

3. The method according to claim 1, characterized in that, The step of determining the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each of the inspection items includes: Based on the predicted heat capacity corresponding to each of the items to be inspected, candidate items to be inspected whose predicted heat capacity is less than the preset warning heat capacity are determined from a plurality of items to be inspected; If the candidate items to be inspected are not empty, then the candidate item to be inspected with the shortest device occupancy time is determined as the target item to be inspected; If the candidate items to be inspected are empty, then the minimum cooling time corresponding to the CT equipment is calculated based on the lowest heat load, the current heat capacity, and the warning heat capacity in the items to be inspected. After the CT equipment has waited for the minimum cooling time, the item to be inspected corresponding to the minimum heat load is determined as the target item to be inspected.

4. The method according to claim 3, characterized in that, The step of calculating the minimum cooling time corresponding to the CT equipment based on the minimum heat load of the item to be inspected, the current heat capacity, and the warning heat capacity includes: The minimum cooling time for the CT device is calculated using the following formula: in, The minimum cooling time is given by k, where k is the cooling coefficient of the X-ray tube corresponding to the CT equipment. For the aforementioned warning heat capacity, For the minimum heat load, This refers to the current heat capacity.

5. The method according to claim 1, characterized in that, The method further includes: When the current heat capacity is in the preset low heat range, the item with the highest heat load and the longest equipment occupation time among all the items to be inspected is determined as the target item to be inspected by the CT equipment at present. If the current heat capacity is within a preset warning range, the CT device will be controlled to stop working until the current heat capacity reaches the high-efficiency heat dissipation range. When the current heat capacity is within a preset shutdown range, the CT equipment is controlled to shut down.

6. The method according to claim 5, characterized in that, The low-heat zone is less than the low-temperature heat capacity, the high-efficiency heat dissipation zone is greater than or equal to the low-temperature heat capacity and less than the warning heat capacity, the warning zone is greater than or equal to the warning heat capacity and less than the shutdown heat capacity, and the shutdown zone is greater than or equal to the shutdown heat capacity.

7. An intelligent scheduling device for CT equipment, characterized in that, Applied to a server, the server being communicatively connected to at least one CT device, the device includes: The acquisition module is used to acquire the current thermal capacity of the CT device when the CT device is in an idle state. The calculation module is used to calculate the predicted heat capacity after performing the examination under the current heat capacity, based on the current heat capacity and the examination data corresponding to the examination items in the waiting pool of the CT equipment, when the current heat capacity is within a preset high-efficiency heat dissipation range. The determination module is used to determine the target inspection item to be performed by the CT equipment based on the predicted heat capacity corresponding to each of the inspection items.

8. The apparatus according to claim 7, characterized in that, The inspection data includes the heat load and equipment occupancy time corresponding to the items to be inspected. The calculation module is also used to calculate the predicted heat capacity for each item to be inspected in the waiting pool of the CT equipment using the following formula: in, For the current heat capacity, The equipment occupancy time corresponding to the item to be inspected. The cooling coefficient of the X-ray tube corresponding to the CT equipment. The heat load corresponding to the item to be inspected.

9. A server, characterized in that, It includes a processor and a memory, the memory storing a computer program executable by the processor to implement the method of any one of claims 1-6.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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