Target spot quantity determination method, electronic equipment and storage medium

Abstract

The invention provides a target spot number determination method, electronic equipment and a storage medium, relates to the technical field of medical treatment, is used for reasonably and accurately determining the maximum target spot number, and can support efficient and accurate optimization of a treatment plan. The method comprises the following steps: acquiring the volume and shape characteristic parameters of a target region to be treated; the shape feature parameters are used for reflecting the complexity of the shape of the to-be-treated target region; according to the volume of the to-be-treated target region, determining the number of initial target spots of the to-be-treated target region; the number of the initial target spots is the number of one or more collimators in one group; a combination of a set of one or more beam focal spot volumes corresponding to a set of one or more collimators; determining the number of target spots of the to-be-treated target region based on the number of the initial target spots and the shape feature parameters; the number of the target spots is in positive correlation with the shape feature parameters; the number of the target spots is used for representing the maximum number of the target spots allowed to be deployed in the target area to be treated.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a method for determining the number of target points, an electronic device, and a storage medium. Background Art

[0002] Gamma-ray stereotactic therapy in radiotherapy is an effective method for treating tumors. The gamma-ray stereotactic radiotherapy system (also known as the "gamma knife") can focus gamma rays so that the target area at the focal point receives a high dose of radiation, while the surrounding healthy tissues receive a lower dose.

[0003] When treatment is performed using a gamma-ray stereotactic radiotherapy system, collimators of different sizes are usually used to shape the rays reaching different positions in the target area into approximate "spheres" (also called target points) of different diameters. The target area is filled with these target points, and by assigning different weights to these target points, the dose field formed by the superposition of all target points in the target area can cover as much of the target area as possible while minimizing damage to normal tissues, thereby achieving radiotherapy for the patient.

[0004] At present, the automatic planning algorithm can generally be used to find the optimal number of targets under the maximum number of targets given based on manual experience. If the maximum number of targets given based on manual experience is large, it may take a long time to generate a treatment plan with good quality, and it may easily lead to a large number of targets in the treatment plan generated by the automatic plan, causing damage to normal tissue. If the maximum number of targets given based on manual experience is small, it may lead to the inability to generate a qualified treatment plan, resulting in a small number of targets in the treatment plan generated by the automatic plan, and it is impossible to achieve effective radiotherapy of the target area. Therefore, it is necessary to reasonably and accurately determine the maximum number of targets. Summary of the invention

[0005] The present application provides a method for determining the number of targets, an electronic device, and a storage medium, which can reasonably and accurately determine the maximum number of targets and support efficient and accurate optimization of treatment plans.

[0006] In a first aspect, the present application provides a method for determining the number of target points, comprising: obtaining the volume of a target area to be treated, and shape characteristic parameters. The shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated. According to the volume of the target area to be treated, the initial number of target points in the target area to be treated is determined. The initial number of target points is the number of a group of one or more collimators. A combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. Based on the initial number of target points and the shape characteristic parameters, the number of target targets in the target area to be treated is determined. The number of target targets is positively correlated with the shape characteristic parameters. The number of target targets is used to indicate the maximum number of targets allowed to be deployed in the target area to be treated.

[0007] In some embodiments, the method for determining the initial number of target points in the target area to be treated according to the volume of the target area to be treated specifically includes: obtaining multiple beam focal spot volumes corresponding to collimators of different sizes. Based on the volume of the target area to be treated and the multiple beam focal spot volumes, the initial number of target points is determined.

[0008] In some embodiments, the method for determining the number of initial target points based on the volume of the target area to be treated and the multiple beam focal spot volumes specifically includes: determining the number of collimators corresponding to the current beam focal spot volume that can be accommodated in the current remaining volume of the target area to be treated in descending order of the multiple beam focal spot volumes, and obtaining the number of collimators of different sizes. The sum of the numbers of collimators of different sizes is determined as the number of initial target points.

[0009] In some embodiments, the shape characteristic parameters include at least one of the following: a hole characteristic parameter of the target area to be treated, an intersection area characteristic parameter between continuous multi-layer target area slices of the target area to be treated, and a relative position characteristic parameter between continuous multi-layer target area slices. The hole characteristic parameter is positively correlated with the number of holes existing in the target area to be treated. The intersection area characteristic parameter is positively correlated with the number of direction changes of the intersection area change trend between continuous multi-layer target area slices, and the intersection area change trend is the size change trend of the intersection area between each two adjacent layers of target area slices. The relative position characteristic parameter is the consistency of the area change trend corresponding to the continuous multi-layer target area slices. The area change trend consistency is used to indicate whether the intersection area change trend and the slice area change trend are consistent. The slice area change trend is the size change trend of the slice area between each two adjacent layers of target area slices.

[0010] In some embodiments, the method for obtaining shape characteristic parameters of the target area to be treated specifically includes: obtaining slice images of each of the continuous multi-layer target area slices of the target area to be treated, and determining the shape characteristic parameters based on the slice images of each of the continuous multi-layer target area slices.

[0011] In some embodiments, when the shape feature parameters include hole feature parameters, the method for determining the shape feature parameters based on the slice images of each of the continuous multi-layer target slices specifically includes: determining whether each layer of the target slice has holes based on the target edge contour in each layer of the slice image. In the case that there are target slices with holes in the continuous multi-layer target slices, determining the target irregularity from the irregularities of each of the continuous multi-layer target slices as the hole feature parameter. The greater the irregularity of the target slice, the greater the probability of being determined as the target irregularity. The irregularity of each layer of the target slice is determined based on the valid rows, valid columns, target rows and target columns in the slice images of each layer of the target slice. The valid rows are used to indicate the rows in which there are pixels located on the target edge contour in the entire row of pixels. The valid columns are used to indicate the columns in which there are pixels located on the target edge contour in the entire column of pixels. The target rows are used to indicate the rows in which the number of pixels located on the target edge contour in the entire row of pixels is greater than a preset number. The target columns are used to indicate the columns in which the number of pixels located on the target edge contour in the entire column of pixels is greater than a preset number. When there is no target area slice with a hole in the continuous multi-layer target area slices, the preset value is determined as the hole characteristic parameter.

[0012] In some embodiments, based on the target area edge contour in each slice image, the method for determining whether each layer of the target area slice has a hole specifically includes: when the ratio of the target row in the valid row is greater than a preset ratio, or the ratio of the target column in the valid column is greater than a preset ratio, determining that the target area slice has a hole. When the ratio of the target row in the valid row is less than or equal to the preset ratio, and the ratio of the target column in the valid column is less than or equal to the preset ratio, determining that the target area slice does not have a hole.

[0013] In some embodiments, the irregularity of each target slice is the ratio of the sum of the number of target rows and the number of target columns to the sum of the number of valid rows and the number of valid columns.

[0014] In some embodiments, when the shape characteristic parameters include intersection area characteristic parameters, the method for determining the shape characteristic parameters based on the slice images of each of the continuous multi-layer target slices specifically includes: determining the intersection pixels between each two adjacent slice images in the continuous multi-layer slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located within the target slice. Based on the intersection pixels between each two adjacent slice images, determine the first fitting result corresponding to the intersection area change trend. Determine the number of continuous monotonic intervals in the first fitting result as the intersection area characteristic parameter.

[0015] In some embodiments, when the shape feature parameters include relative position feature parameters, the method for determining the shape feature parameters based on the slice images of each of the continuous multi-layer target slices specifically includes: determining the second fitting result corresponding to the slice area change trend based on the target pixels in each slice image. When the second fitting result and the first fitting result meet the preset conditions, the first consistency is determined as the relative position feature parameter. The first fitting result is determined based on the intersection pixels between each two adjacent slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice. The preset conditions include that the number of continuous monotonic intervals is the same and the slice images corresponding to the continuous monotonic intervals are the same. The first consistency is used to indicate that the intersection area change trend is consistent with the slice area change trend. When the second fitting result and the first fitting result do not meet the preset conditions, the second consistency is determined as the relative position feature parameter. The second consistency is used to indicate that the intersection area change trend is inconsistent with the slice area change trend.

[0016] In some embodiments, the method for determining the number of target targets in the target area to be treated based on the initial number of target points and the shape characteristic parameters specifically includes: determining the number of characteristic target points based on the initial number of target points and the shape characteristic parameters. The number of characteristic target points includes at least one of the following: the first number of target points determined according to the initial number of target points, the hole characteristic parameter and the first coefficient, the second number of target points determined according to the intersection area characteristic parameter and the second coefficient, and the third number of target points determined according to the initial number of target points, the relative position characteristic parameter and the third coefficient. The number of target targets is determined based on the initial number of target points and the number of characteristic target points.

[0017] In a second aspect, the present application provides a device for determining the number of target points, comprising: an acquisition unit and a processing unit.

[0018] The acquisition unit is used to acquire the volume of the target area to be treated and the shape characteristic parameters. The shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated. The processing unit is used to determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated. The initial number of target points is the number of a group of one or more collimators. The combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. The processing unit is also used to determine the number of target targets in the target area to be treated based on the initial number of target points and the shape characteristic parameters. The number of target targets is positively correlated with the shape characteristic parameters. The number of target targets is used to indicate the maximum number of targets allowed to be deployed in the target area to be treated.

[0019] In some embodiments, the processing unit is specifically configured to: obtain multiple beam focal spot volumes corresponding to collimators of different sizes, and determine the number of initial target points based on the volume of the target area to be treated and the multiple beam focal spot volumes.

[0020] In some embodiments, the processing unit is specifically used to: determine the number of collimators corresponding to the current beam focal spot volume that can be accommodated in the current remaining volume of the target area to be treated in order from large to small of the multiple beam focal spot volumes, and obtain the number of collimators of different sizes. The sum of the numbers of collimators of different sizes is determined as the initial target point number.

[0021] In some embodiments, the shape characteristic parameters include at least one of the following: a hole characteristic parameter of the target area to be treated, an intersection area characteristic parameter between continuous multi-layer target area slices of the target area to be treated, and a relative position characteristic parameter between continuous multi-layer target area slices. The hole characteristic parameter is positively correlated with the number of holes existing in the target area to be treated. The intersection area characteristic parameter is positively correlated with the number of direction changes of the intersection area change trend between continuous multi-layer target area slices, and the intersection area change trend is the size change trend of the intersection area between each two adjacent layers of target area slices. The relative position characteristic parameter is the consistency of the area change trend corresponding to the continuous multi-layer target area slices. The area change trend consistency is used to indicate whether the intersection area change trend and the slice area change trend are consistent. The slice area change trend is the size change trend of the slice area between each two adjacent layers of target area slices.

[0022] In some embodiments, the acquisition unit is specifically used to: acquire slice images of each of the continuous multi-layer target area slices of the target area to be treated, and determine the shape feature parameters based on the slice images of each of the continuous multi-layer target area slices.

[0023] In some embodiments, the acquisition unit is specifically used to: determine whether each layer of target area slice has holes based on the target area edge contour in each layer of slice image. In the case that there are target area slices with holes in the continuous multi-layer target area slices, the target irregularity is determined from the irregularities of the continuous multi-layer target area slices as the hole feature parameter. The greater the irregularity of the target area slice, the greater the probability of being determined as the target irregularity. The irregularity of each layer of target area slice is determined based on the valid rows, valid columns, target rows and target columns in the slice image of each layer of target area slice. The valid row is used to indicate the row where there are pixels located on the target area edge contour in the whole row of pixels. The valid column is used to indicate the column where there are pixels located on the target area edge contour in the whole column of pixels. The target row is used to indicate the row where the number of pixels located on the target area edge contour in the whole row of pixels is greater than the preset number. The target column is used to indicate the column where the number of pixels located on the target area edge contour in the whole column of pixels is greater than the preset number. In the case that there are no target area slices with holes in the continuous multi-layer target area slices, the preset value is determined as the hole feature parameter.

[0024] In some embodiments, the acquisition unit is specifically configured to: determine that the target area slice has holes when the ratio of the target rows in the valid rows is greater than a preset ratio, or the ratio of the target columns in the valid columns is greater than a preset ratio. Determine that the target area slice does not have holes when the ratio of the target rows in the valid rows is less than or equal to the preset ratio, and the ratio of the target columns in the valid columns is less than or equal to the preset ratio.

[0025] In some embodiments, the irregularity of each target slice is the ratio of the sum of the number of target rows and the number of target columns to the sum of the number of valid rows and the number of valid columns.

[0026] In some embodiments, the acquisition unit is specifically used to: determine the intersection pixels between each two adjacent slice images in the continuous multi-layer slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice. Based on the intersection pixels between each two adjacent slice images, a first fitting result corresponding to the intersection area change trend is determined. The number of continuous monotonic intervals in the first fitting result is determined as the intersection area characteristic parameter.

[0027] In some embodiments, the acquisition unit is specifically used to: determine the second fitting result corresponding to the slice area change trend based on the target area pixels in each layer of slice image. When the second fitting result meets the preset conditions with the first fitting result, the first consistency is determined as the relative position feature parameter. The first fitting result is determined based on the intersection pixels between each two adjacent slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located within the target slice. The preset conditions include that the number of continuous monotonic intervals is the same and the slice images corresponding to the continuous monotonic intervals are the same. The first consistency is used to indicate that the intersection area change trend is consistent with the slice area change trend. When the second fitting result does not meet the preset conditions with the first fitting result, the second consistency is determined as the relative position feature parameter. The second consistency is used to indicate that the intersection area change trend is inconsistent with the slice area change trend.

[0028] In some embodiments, the processing unit is specifically configured to: determine the number of characteristic target points based on the initial number of target points and the shape characteristic parameters. The number of characteristic target points includes at least one of the following: the first number of target points determined according to the initial number of target points, the hole characteristic parameter and the first coefficient, the second number of target points determined according to the intersection area characteristic parameter and the second coefficient, and the third number of target points determined according to the initial number of target points, the relative position characteristic parameter and the third coefficient. The number of target targets is determined according to the initial number of target points and the number of characteristic target points.

[0029] In a third aspect, the present application provides an electronic device, the electronic device comprising: a processor, and a memory configured to store processor executable instructions, wherein the processor is configured to execute instructions to implement any possible method for determining the number of target points as described in the first aspect above.

[0030] In a fourth aspect, the present application provides a non-volatile storage medium having a computer program stored thereon. When the computer program is read and executed, any possible method for determining the number of targets described in the first aspect above is implemented.

[0031] In a fifth aspect, the present application provides a computer program product, which includes computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes any possible target quantity determination method as described in the first aspect.

[0032] These and other aspects of the present application will become more apparent from the following description.

[0033] The technical solution provided by this application brings at least the following beneficial effects:

[0034] In the present application, the electronic device can obtain the volume of the target area to be treated, and determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated. Since the initial number of target points is the number of a group of one or more collimators, and the combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. Therefore, the initial number of target points determined by the electronic device in the embodiment of the present application can accurately match the volume of the target area to be treated.

[0035] In addition, the electronic device can obtain the shape characteristic parameters of the target area to be treated, and further determine the maximum number of targets allowed to be deployed in the target area to be treated based on the initial number of target points and the shape characteristic parameters. Since the shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated, and the number of target targets is positively correlated with the shape characteristic parameters. Therefore, in the embodiment of the present application, the electronic device can determine the number of target targets based on the initial number of target points that matches the volume of the target area to be treated, combined with the complexity of the shape of the target area to be treated, so that the number of target targets can accurately match the volume and shape characteristics of the target area to be treated, can adapt to the uneven target phenomenon caused by the complex shape of the target area to be treated, and has higher rationality.

[0036] Based on this, compared with the method of giving the maximum number of targets based on manual experience, the number of target targets determined by this application can support automatic planning, without missing the optimal number of targets, to optimize the treatment plan based on a smaller maximum number of targets as much as possible, thereby improving the efficiency of finding the optimal number of targets. In summary, this application can be used to reasonably and accurately determine the maximum number of targets, and can support the efficient and accurate optimization of treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0038] Figure 1 A schematic diagram of the structure of a radiotherapy system provided in an embodiment of the present application;

[0039] Figure 2 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application;

[0040] Figure 3 A schematic diagram of a process for determining the number of target points provided in an embodiment of the present application;

[0041] Figure 4 A schematic diagram of a flow chart of another method for determining the number of target points provided in an embodiment of the present application;

[0042] Figure 5 A schematic diagram of a flow chart of another method for determining the number of target points provided in an embodiment of the present application;

[0043] Figure 6 A schematic diagram of a flow chart of another method for determining the number of target points provided in an embodiment of the present application;

[0044] Figure 7 A schematic diagram of the structure of a device for determining the number of target points provided in an embodiment of the present application;

[0045] Figure 8 A schematic diagram of the structure of another device for determining the number of target points provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] The target point quantity determination method, electronic device and storage medium provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0047] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0048] It should be noted that, in the embodiments of the present application, words such as "exemplarily" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present related concepts in a specific way.

[0049] The term "and / or" used in the present application includes using either or both methods at the same time.

[0050] The terms "first", "second" and "third" etc. in the specification and drawings of this application are used to distinguish different objects, rather than to describe the specific order of the objects, nor to indicate or imply relative importance or implicitly indicate the number of the indicated technical features.

[0051] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0052] The following is an explanation of some concepts involved in a method for determining the number of target points, an electronic device, and a storage medium provided in an embodiment of the present application.

[0053] With the development of radiotherapy technology, automatic planning methods based on reinforcement learning have been applied. Automatic planning can quickly generate qualified treatment plans and can efficiently generate a large number of relatively accurate treatment plans. In the process of generating treatment plans using automatic planning, the maximum number of targets in the target area needs to be given in advance. Then the automatic planning algorithm can find the optimal number of targets, target positions, target weights, and target models within the given maximum number of targets, so as to find a set of treatment plans with a large coverage rate (such as greater than or equal to 95%) and a large selection rate (such as greater than or equal to 80%) for the target area as much as possible.

[0054] It can be seen that the quality of the treatment plan generated by the automatic plan is strongly related to the maximum number of targets in the given target area. If the maximum number of targets in the given target area is small, it may result in the inability to generate a qualified treatment plan, and it is easy to result in a small number of targets in the treatment plan generated by the automatic plan, and it is impossible to achieve effective radiotherapy of the target area. If the maximum number of targets in the given target area is large, it may take a long time to generate a treatment plan with good quality, and it is easy to result in a large number of targets in the treatment plan generated by the automatic plan, causing damage to normal tissue. Therefore, it is necessary to reasonably and accurately determine the maximum number of targets.

[0055] Based on this, in order to reasonably and accurately determine the maximum number of targets, an embodiment of the present application provides a method for determining the number of targets, an electronic device, and a storage medium. In the present application, the electronic device can obtain the volume of the target area to be treated, and determine the initial number of targets in the target area to be treated based on the volume of the target area to be treated. Since the initial number of targets is the number of a group of one or more collimators, and the combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. Therefore, the initial number of targets determined by the electronic device in the embodiment of the present application can accurately match the volume of the target area to be treated.

[0056] In addition, the electronic device can obtain the shape characteristic parameters of the target area to be treated, and further determine the maximum number of targets allowed to be deployed in the target area to be treated based on the initial number of target points and the shape characteristic parameters. Since the shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated, and the number of target targets is positively correlated with the shape characteristic parameters. Therefore, in the embodiment of the present application, the electronic device can determine the number of target targets based on the initial number of target points that matches the volume of the target area to be treated, combined with the complexity of the shape of the target area to be treated, so that the number of target targets can accurately match the volume and shape characteristics of the target area to be treated, can adapt to the uneven target phenomenon caused by the complex shape of the target area to be treated, and has higher rationality.

[0057] Based on this, compared with the method of giving the maximum number of targets based on manual experience, the number of target targets determined by this application can support automatic planning, without missing the optimal number of targets, to optimize the treatment plan based on a smaller maximum number of targets as much as possible, thereby improving the efficiency of finding the optimal number of targets. In summary, this application can be used to reasonably and accurately determine the maximum number of targets, and can support the efficient and accurate optimization of treatment plans.

[0058] The method for determining the number of targets can be applied to electronic devices. The electronic device can be a device that has the functions of formulating, optimizing, and evaluating radiotherapy plans (for example, a treatment planning system (TPS)), or it can exist as an independently operated device for providing the maximum number of targets to the treatment planning system. The embodiments of the present application are not limited to this.

[0059] like Figure 1 , which is a schematic diagram of the structure of a radiotherapy system provided in an embodiment of the present application. The radiotherapy system 100 may include an electronic device 101, a control device 102 and a radiotherapy device 103. The control device 102 may be connected to the electronic device 101 and the radiotherapy device 103 respectively.

[0060] In some embodiments, the electronic device 101 may be a treatment planning system (TPS), including a TPS client and a TPS server.

[0061] The TPS client may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop computer. For example, in some embodiments, the user can trigger the TPS server to execute the target number determination, treatment plan optimization, and other processes of the present application through the radiotherapy planning system running on the TPS server through the TPS client, and display the optimized treatment plan. In this way, the user's time can be effectively saved, and the optimized treatment plan can be presented more intuitively so that the user can evaluate the treatment plan.

[0062] Among them, the TPS server can be an independent physical server, or a server cluster or distributed file system composed of multiple physical servers, or at least one of the cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks, and big data or artificial intelligence platforms, etc., which is not limited by the embodiments of the present disclosure. In some embodiments, the number of the above-mentioned TPS servers can be more or less, which is not limited by the embodiments of the present disclosure. Of course, the TPS server can also include other functions to provide more comprehensive and diversified services. In some embodiments, the TPS server is used to provide background services for the above-mentioned TPS client, such as executing the target number determination and treatment plan optimization process of this application.

[0063] In some embodiments, the control device 102 is a device for controlling the radiotherapy device 103 to execute the treatment plan. In some embodiments, the control device 102 may include a host computer and a slave computer, the host computer is used to interact with the user, and the slave computer is used to control the movement of each moving part in the radiotherapy device 103. The host computer may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, a laptop computer and / or a server device, and the slave computer may be a control device such as a programmable logic controller (PLC).

[0064] In some embodiments, the radiotherapy device 103 can be used to irradiate the target area to be treated with therapeutic radiation. For example, the radiotherapy device 103 can be a gamma knife or other device. Figure 1 What is shown is only an example of the device form of the radiotherapy device 103. The embodiments of the present application are not limited to this. In one embodiment of the present disclosure, the electronic device 101 can determine the volume of the target area to be treated and the shape characteristic parameters based on the image information of the target area to be treated, and determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated, so as to further determine the number of target targets in the target area to be treated based on the initial number of target points and the shape characteristic parameters, that is, determine the maximum number of targets deployed in the target area to be treated, and then generate a treatment plan based on the maximum number of targets. In addition, the electronic device 101 can send the generated treatment plan to the control device 102. The control device 102 can receive the treatment plan from the electronic device 101, and control the radiotherapy device 103 to emit a beam to the target area to be treated based on the received treatment plan.

[0065] Figure 2 The hardware structure diagram of an electronic device 101 provided in an embodiment of the present application is shown in FIG. The electronic device 101 may include a display screen 1011, a processor 1012, a memory 1013, and a communication interface 1014. The display screen 1011, the processor 1012, the memory 1013, and the communication interface 1014 may be interconnected via a bus 1015.

[0066] The display screen 1011 may be a micro organic electroluminescence display (OLED) display, a liquid crystal on silicon (LCOS) display, etc. The display screen 1011 may be used to display image information of a target area, etc.

[0067] The processor 1012 may be one or more central processing units (CPUs). When the processor 1012 is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor 1012 may be used to read data stored in the memory 1013 and perform processing such as image recognition and rendering.

[0068] The memory 1013 may be a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or a compact disc read-only memory (CD-ROM).

[0069] The communication interface 1014 is used to receive / send data in response to instructions from the processor 1012 and the memory 1013 .

[0070] The bus 1015 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus 1015 may be divided into an address bus, a data bus, a control bus, etc.

[0071] The embodiment of the present application does not limit the number of these components. For example, the electronic device 101 may include one or more display screens 1011. For another example, the electronic device 101 may include one or more processors 1012. For another example, the electronic device 101 may include one or more memories 1013, etc.

[0072] The following is a description of the method for determining the number of targets provided in the embodiments of the present application.

[0073] like Figure 3 As shown, it is a flow chart of a method for determining the number of target points provided in an embodiment of the present application. The execution subject of the method can be Figure 1 or Figure 2 The electronic device in the method includes: S201-S203.

[0074] S201, obtaining the volume and shape characteristic parameters of the target area to be treated.

[0075] The target area to be treated may be an area that needs to be irradiated to achieve tumor treatment. The area may include tumor tissue, or further include surrounding tissue of the tumor tissue, etc. It should be understood that the target area to be treated may also be referred to as a tumor target area or a planned target area, etc., without limitation.

[0076] The volume of the target area to be treated is the size of the space occupied by the diseased tissue that needs to be radiotherapy.

[0077] The shape characteristic parameter of the target area to be treated is used to reflect the complexity of the shape of the target area to be treated.

[0078] In one possible manner, the electronic device may determine the volume and shape characteristic parameters of the target area to be treated based on the image information of the target area to be treated.

[0079] For example, the electronic device can segment the image containing the target area to be treated to determine the boundary of the target area to be treated. Then, the volume of the target area to be treated is determined. Optionally, the image of the target area to be treated can be a magnetic resonance (MR) image or a computed tomography (CT) image. The image of the target area to be treated includes multi-layer target area slice images of the target area to be treated continuously acquired along a certain anatomical direction.

[0080] For another example, the electronic device can determine the shape characteristic parameters of the target area to be treated based on the multi-layer target area slice image. The implementation of this process can refer to the specific description in S2011-S2012 below, which will not be repeated here.

[0081] Among them, the shape characteristic parameters of the target area to be treated may include at least one of the hole characteristic parameters of the target area to be treated, the intersection area characteristic parameters between continuous multi-layer target area slices to be treated, and the relative position characteristic parameters between continuous multi-layer target area slices.

[0082] The hole characteristic parameters of the target area to be treated are positively correlated with the number of holes existing in the target area to be treated.

[0083] The characteristic parameter of the intersection area between the continuous multi-layer target area slices of the target area to be treated is positively correlated with the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices. The intersection area change trend is the size change trend of the intersection area between each two adjacent target area slices.

[0084] The relative position characteristic parameter between the continuous multi-layer target area slices is the area change trend consistency corresponding to the continuous multi-layer target area slices. The area change trend consistency is used to indicate whether the intersection area change trend and the slice area change trend are consistent. The slice area change trend is the size change trend of the slice area between each two adjacent target area slices.

[0085] S202: Determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated.

[0086] The number of initial target points is the number of a group of one or more collimators. A combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated.

[0087] Among them, a beam focal spot corresponding to a collimator is formed at the focal position after the beam emitted by the radiation source passes through a collimator of the same size as the collimator. Further, the combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated, which means that: when the individual beam focal spots in the group of one or more beam focal spots corresponding to the group of one or more collimators do not overlap with each other, the sum of the volumes of the individual beam focal spots in the group of beam focal spots matches the volume of the target area to be treated.

[0088] In one possible manner, the sum of the volumes of the individual beam focal spots in the group of beam focal spots matches the volume of the target area to be treated. The morphology of the volume formed by the combination of the individual beam focal spots in the group of beam focal spots may be roughly the same as the morphology of the volume of the target area to be treated, or the difference value of the sum of the volumes of the individual beam focal spots in the group of beam focal spots relative to the volume of the target area to be treated meets a preset difference threshold. For example, the preset difference threshold may be 1% or 3%. In this way, the sum of the volumes of a group of one or more beam focal spots corresponding to a group of one or more collimators has a small difference with the volume of the target area to be treated, and the group of one or more beam focal spots can better cover the target area to be treated, and can produce a better treatment effect.

[0089] Thus, the number of the one or more beam focal spots in the group is the maximum number of beam focal spots allowed to be accommodated in the target area to be treated, that is, the maximum number of target points allowed to be deployed, that is, the initial number of target points. It should be understood that the volumes of different beam focal spots can be different or the same. That is, the sizes of different collimators in a group of one or more collimators can be the same or different.

[0090] It should be understood that the collimator is used to limit and adjust the shape and direction of the beam, and the beam passing through the collimator will form a beam focal spot in space. The size of the beam focal spot volume depends on the size of the collimator. For ease of understanding, the embodiments of the present application are described by taking collimators of different sizes producing beam focal spots of different volumes, and collimators of the same size producing beam focal spots of the same volume as an example.

[0091] Optionally, when the electronic device determines the number of initial target points of the target area to be treated according to the volume of the target area to be treated, the shape of the target area to be treated may be considered, and the target area to be treated may be filled with collimators of different sizes. In this way, the electronic device may determine the number of a group of one or more collimators as the number of initial target points when the beam focal spots corresponding to the group of one or more collimators cover the target area to be treated well.

[0092] Alternatively, the electronic device may obtain multiple beam focal spot volumes corresponding to collimators of different sizes, and determine the initial number of target points based on the volume of the target area to be treated and the multiple beam focal spot volumes. The implementation of this process may refer to the specific description in S2021-S2022 below, which will not be repeated here.

[0093] S203: Determine the number of target points in the target area to be treated based on the initial number of target points and shape characteristic parameters.

[0094] The target number of targets is used to indicate the maximum number of targets allowed to be deployed in the target area to be treated, and is used to support the automatic planning algorithm to accurately find the optimal number of targets.

[0095] The number of target points is positively correlated with the shape characteristic parameter. For example, the electronic device may multiply the initial number of target points and the shape characteristic parameter to obtain the number of target targets in the target area to be treated. For another example, the electronic device may perform a weighted summation of the initial number of target points and the shape characteristic parameter to obtain the number of target targets in the target area to be treated. The embodiments of the present application are not limited to this.

[0096] In one embodiment, combining Figure 3 The method for determining the number of targets shown in Figure 4 As shown, it is a flow chart of another method for determining the number of target points provided by an embodiment of the present application. In the above S202, that is, when the electronic device determines the initial number of target points in the target area to be treated according to the volume of the target area to be treated, the embodiment of the present application provides an optional implementation method, including: S2021-S2022.

[0097] S2021. Obtain multiple beam focal spot volumes corresponding to collimators of different sizes.

[0098] Among them, collimators of different sizes correspond to different beam focal spot volumes.

[0099] S2022. Determine the number of initial target points based on the volume of the target area to be treated and the volumes of multiple beam focal spots.

[0100] For example, the electronic device may determine an average value of multiple beam focal spot volumes as the average beam focal spot volume. Further, the electronic device may determine a quotient obtained by dividing the volume of the target area to be treated by the average beam focal spot volume as the initial target point number.

[0101] For another example, the electronic device may determine the number of collimators corresponding to the current beam focal spot volume that can be accommodated in the current remaining volume of the target area to be treated in order from large to small according to the multiple beam focal spot volumes, and obtain the number of collimators of different sizes. Furthermore, the electronic device may determine the sum of the numbers of collimators of different sizes as the number of initial target points. It should be understood that in the process of performing multiple calculations in order from large to small according to the multiple beam focal spot volumes, the current remaining volume of the target area to be treated in the first calculation is the volume of the target area to be treated, and the current beam focal spot volume is the beam focal spot volume with the largest median value among the multiple beam focal spot volumes.

[0102] For example, it is assumed that the beam focal spot volume corresponding to the collimator of size 1 is V18, the beam focal spot volume corresponding to the collimator of size 2 is V14, the beam focal spot volume corresponding to the collimator of size 3 is V8, and the beam focal spot volume corresponding to the collimator of size 3 is V4. Among them, V18 is greater than V14, V14 is greater than V8, and V8 is greater than V4.

[0103] Then the electronic device can determine the quotient of the volume of the target area to be treated divided by V18 as the first quantity, and obtain the remainder a. The first quantity is the number of collimators of size 1 corresponding to the beam focal spot volume V18. The remainder a is the current remaining volume of the target area to be treated. Then, the electronic device can determine the quotient of remainder a divided by V14 as the second quantity, and obtain the remainder b. The second quantity is the number of collimators of size 2 corresponding to the beam focal spot volume V14. The remainder b is the current remaining volume of the target area to be treated. Then, the electronic device can determine the quotient of remainder b divided by V8 as the third quantity, and obtain the remainder c. The third quantity is the number of collimators of size 3 corresponding to the beam focal spot volume V8. The remainder c is the current remaining volume of the target area to be treated. Then, the electronic device can determine the quotient of remainder c divided by V4 as the fourth quantity. The fourth quantity is the number of collimators of size 4 corresponding to the beam focal spot volume V4. Furthermore, the electronic device can determine the sum of the first number, the second number, the third number and the fourth number as the initial target point number when there is no remainder when the remainder c is divided by V4 or there is no collimator of a smaller size.

[0104] Or further, the electronic device can determine the first value (such as 1 or 2) as the fifth number when there is a remainder when the remainder c is divided by V4 and there is no collimator of a smaller size. Furthermore, the electronic device can determine the sum of the first number, the second number, the third number, the fourth number and the fifth number as the initial target point number.

[0105] Alternatively, the electronic device can continue to select a collimator with a beam focal spot volume smaller than V4 for calculation if there is a remainder when the remainder c is divided by V4 and a collimator with a smaller size exists. The specific calculation process is similar to the above and will not be described in detail.

[0106] In one embodiment, combining Figure 3 The method for determining the number of targets shown in Figure 5 FIG. 2 is a flow chart of another method for determining the number of target points provided by an embodiment of the present application. In the above S201, when the electronic device obtains the shape characteristic parameters of the target area to be treated, the embodiment of the present application provides an optional implementation method, including: S2011-S2012.

[0107] S2011, obtaining slice images of each of the continuous multi-layer target area slices of the target area to be treated.

[0108] S2012. Determine shape feature parameters based on the slice images of each of the continuous multi-layer target area slices.

[0109] For example, when the shape characteristic parameter of the target area to be treated is a hole characteristic parameter, the electronic device can use the slice images of each layer of the target area slice to identify whether there are holes in the target area to be treated, and then determine the hole characteristic parameter of the target area to be treated. The hole characteristic parameter can be positively correlated with the number of holes in the target area to be treated. That is, the larger the number of holes in the target area to be treated, the larger the hole characteristic parameter. In other words, the hole characteristic parameter can be used to indicate the number of holes in the target area to be treated. The larger the hole characteristic parameter, the larger the number of holes in the target area to be treated, and the higher the shape complexity of the target area to be treated.

[0110] For another example, when the shape characteristic parameter of the target area to be treated is an intersection area characteristic parameter, the electronic device can determine the intersection area between each two adjacent target area slices based on the slice images of each layer of target area slices, so as to further determine the intersection area characteristic parameter between the continuous multi-layer target area slices of the target area to be treated. The intersection area characteristic parameter is positively correlated with the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices. The intersection area change trend is the size change trend of the intersection area between each two adjacent target area slices. That is, the greater the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices, the greater the intersection area characteristic parameter.

[0111] If the intersection area change trend between the continuous multi-layer target area slices changes from an increasing intersection area to a decreasing intersection area, it can be indicated that the target area to be treated is approximately elliptical in shape. In this case, the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices is once, and the intersection area characteristic parameter can be small, which is used to indicate that the shape complexity of the target area to be treated is low.

[0112] If the intersection area change trend between the continuous multi-layer target area slices is first changed from the intersection area becoming larger and larger to the intersection area becoming smaller and smaller, then changed to the intersection area becoming larger and larger, and then changed to the intersection area becoming smaller and smaller, it can be indicated that the target area to be treated is approximately gourd-shaped. In this case, the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices is three times, and the intersection area characteristic parameter can be large, which is used to indicate that the shape complexity of the target area to be treated is high.

[0113] For another example, when the shape characteristic parameter of the target area to be treated is a relative position characteristic parameter, the electronic device can determine the area of ​​each layer of target area slices and the intersection area between each two adjacent layers of target area slices based on the slice images of each layer of target area slices, so as to further determine the relative position characteristic parameters between the continuous multi-layer target area slices of the target area to be treated. The relative position characteristic parameter is the consistency of the area change trend corresponding to the continuous multi-layer target area slices. The area change trend consistency is used to indicate whether the intersection area change trend and the slice area change trend are consistent. The slice area change trend is the size change trend of the slice area between each two adjacent layers of target area slices.

[0114] If the intersection area change trend between the continuous multi-layer target area slices is from the intersection area becoming larger and larger to the intersection area becoming smaller and smaller, and the slice area change trend of the continuous multi-layer target area slices is from the slice area becoming larger and larger to the slice area becoming smaller and smaller, it can be shown that the intersection area change trend is consistent with the slice area change trend, and it can be accurately shown that the target area to be treated is approximately elliptical in shape. In this case, the area change trend consistency is high, and the relative position characteristic parameter can be large, which is used to indicate that the shape complexity of the target area to be treated is low.

[0115] If the intersection area change trend between the continuous multi-layer target area slices is from the intersection area becoming larger and larger to the intersection area becoming smaller and smaller, and the slice area change trend of the continuous multi-layer target area slices is that the slice area becomes larger and larger, it can be shown that the intersection area change trend and the slice area change trend are inconsistent, which can accurately indicate that the target area to be treated is not approximately elliptical in shape, but irregular in shape. In this case, the area change trend consistency is low, and the relative position characteristic parameter can be small, which is used to indicate that the shape complexity of the target area to be treated is high.

[0116] In one embodiment, in the above S2012, if the shape feature parameter is a hole feature parameter, the embodiment of the present application provides an optional implementation method, including: S20121-S20123.

[0117] S20121. Determine whether each target area slice has holes based on the target area edge contour in each slice image.

[0118] In one possible manner, the electronic device can identify the target area edge contour of the target area to be treated in each slice image based on a contour detection algorithm. If there are no holes in the target area to be treated in a slice layer, the target area edge contour in the slice image of the slice layer is a closed edge frame. If there are one or more holes in the target area to be treated in a slice layer, the target area edge contour in the slice image of the slice layer is a plurality of closed edge frames.

[0119] Based on this, the electronic device can determine whether each layer of target area slice has holes based on the number of edge boxes included in the target area edge contour in each layer of slice image. If the number of edge boxes included in the target area edge contour in a layer of slice image is equal to 1, then the layer of target area slice does not have holes. If the number of edge boxes included in the target area edge contour in a layer of slice image is greater than 1, then the layer of target area slice has holes.

[0120] In another possible manner, after the electronic device identifies the target area edge contour of the target area to be treated in each slice image based on the contour detection algorithm, it can determine that the rows of each slice image have pixels located on the target area edge contour in the entire row of pixels, and determine that the rows of each slice image have pixels located on the target area edge contour in the entire row of pixels greater than a preset number of pixels. For example, the electronic device can assign the pixels in each slice image where the target area edge contour exists to a first pixel value (such as 1 or 2), and assign the pixels where the target area edge contour does not exist to a second pixel value (such as 0), to obtain a contour matrix for each slice image. Further, based on the contour matrix for each slice image, the electronic device can determine that the rows of each slice image have pixels with a first pixel value in the entire row of pixels, and determine that the rows of each slice image have pixels with a first pixel value in the entire row of pixels greater than a preset number of pixels.

[0121] Furthermore, the electronic device may determine that a column in which the whole column of pixels in each layer of slice image has pixels located on the edge contour of the target area is a valid column, and determine that a column in which the number of pixels located on the edge contour of the target area in the whole column of pixels in each layer of slice image is greater than a preset number is a target column. It should be understood that the implementation method of the electronic device determining the valid column and the target column can be understood by referring to the description of the electronic device determining the valid row and the target row, which will not be described in detail.

[0122] Considering that a row or column with more than two contour lines is more likely to be a row or column where a hole is located, the preset number may be 3, 4 or 5, so as to filter out the target row or column where the hole is located.

[0123] Furthermore, if the ratio of target rows in the effective rows of the slice image of a layer of target area slices is greater than a preset ratio, or the ratio of target columns in the effective columns is greater than a preset ratio, it can be indicated that the layer of target area slices has obvious holes. The electronic device can then determine that the layer of target area slices has holes. If the ratio of target rows in the effective rows of the slice image of a layer of target area slices is less than or equal to a preset ratio, and the ratio of target columns in the effective columns is less than or equal to a preset ratio, it can be indicated that the layer of target area slices may not have holes. The electronic device can then determine that the layer of target area slices does not have holes. The preset ratio can be 0.25 or 0.3.

[0124] S20122. When there are target area slices with holes in the continuous multi-layer target area slices, determine the target irregularity from the respective irregularities of the continuous multi-layer target area slices as the hole feature parameter.

[0125] The greater the irregularity of the target area slice, the greater the probability of being determined as the target irregularity.

[0126] In one possible way, when a layer of target area slices has holes, the electronic device can determine the number of edge boxes included in the target area edge contour in the slice image of the layer of target area slices as the irregularity of the layer of target area slices. In this way, the electronic device can determine the irregularity of each layer of target area slices with holes. Furthermore, the electronic device can determine the target irregularity among the irregularities of each layer of target area slices as the hole feature parameter. For example, the electronic device can determine the irregularity with the largest median value of the irregularities of each layer of target area slices as the target irregularity. For another example, the electronic device can determine the irregularity with the second largest median value of the irregularities of each layer of target area slices as the target irregularity.

[0127] In another possible way, when a layer of target area slices has holes, the electronic device can determine the irregularity of the layer of target area slices based on the valid rows, valid columns, target rows and target columns in the slice image of the layer of target area slices. For example, the electronic device can determine the irregularity of the layer of target area slices by the ratio of the sum of the number of target rows and the number of target columns in the slice image of the layer of target area slices to the sum of the number of valid rows and the number of valid columns. That is, the irregularity of each layer of target area slices is the ratio of the sum of the number of target rows and the number of target columns to the sum of the number of valid rows and the number of valid columns. Furthermore, the electronic device can determine the target irregularity in the irregularity of each layer of target area slices as a hole feature parameter.

[0128] The valid row is used to indicate the row where there are pixels on the edge contour of the target area in the entire row of pixels. The valid column is used to indicate the column where there are pixels on the edge contour of the target area in the entire column of pixels. The target row is used to indicate the row where the number of pixels on the edge contour of the target area in the entire row of pixels is greater than a preset number. The target column is used to indicate the column where the number of pixels on the edge contour of the target area in the entire column of pixels is greater than a preset number.

[0129] S20123. When there is no target area slice with holes in the continuous multi-layer target area slices, determine the preset value as the hole feature parameter.

[0130] If there is no target area slice with holes in the continuous multi-layer target area slices, it can be indicated that there are no holes in the target area to be treated. Then the electronic device can determine that the preset value is the hole characteristic parameter. For example, the preset value can be 0. When the hole characteristic parameter is the preset value, it is used to indicate that there are no holes in the target area to be treated. In this case, there is no need to adjust the initial target point number based on the hole characteristic parameter.

[0131] In one embodiment, in the above S2012, if the shape characteristic parameter is an intersection area characteristic parameter, the embodiment of the present application provides an optional implementation method, including: S20124-S20126.

[0132] S20124. Determine the intersection pixels between every two adjacent slice images in the continuous multi-layer slice images.

[0133] The intersection pixels are used to represent pixels that have the same pixel position between two slice images and are located within the target slice.

[0134] The electronic device can determine the pixels occupied by the target area to be treated in each slice image. Based on this, the electronic device can determine the same pixels between the pixels occupied by the target area to be treated in a slice image of a layer and the pixels occupied by the target area to be treated in a slice image of an adjacent layer of the slice image of the layer as the intersection pixels between the slice image of the layer and the adjacent slice image. In this way, the electronic device can determine the intersection pixels between each two adjacent slice images in the continuous multi-layer slice images.

[0135] S20125. Determine a first fitting result corresponding to a variation trend of an intersection area based on intersection pixels between each two adjacent slice images.

[0136] The intersection pixels between two adjacent slice images may represent the intersection area between two adjacent target slices corresponding to the two adjacent slice images. The intersection area between two adjacent target slices is the area of ​​the overlapping portion between the two adjacent target slices.

[0137] In one possible manner, the electronic device may perform fitting based on the intersection pixels between each two adjacent slice images to determine a first fitting result corresponding to the intersection area change trend. For example, the electronic device may record the acquisition order of the continuous multi-layer slice images from first to last through the horizontal axis of the two-dimensional rectangular coordinate system, and record the intersection pixels between each two adjacent slice images through the vertical axis of the two-dimensional rectangular coordinate system, thereby obtaining the first fitting result.

[0138] In another possible manner, the electronic device can determine the target layer slice image with the largest number of pixels occupied by the target area to be treated in the i-th layer slice image and the i+1-th layer slice image according to the acquisition order of the continuous multi-layer slice images from first to last, and divide the number of intersection pixels of the i-th layer slice image and the i+1-th layer slice image by the number of pixels occupied by the target area to be treated in the target layer slice image to obtain the structural similarity value between the i-th layer slice image and the i+1-th layer slice image. The structural similarity value between two adjacent layers of slice images is used to represent the structural similarity between two adjacent layers of slice images. In this way, the electronic device can determine the structural similarity value between each two adjacent layers of slice images in the continuous multi-layer slice images. Further, the electronic device can subtract the n+1-th structural similarity value from the n-th structural similarity value to obtain the intersection area trend between the slice image corresponding to the n-th structural similarity value and the adjacent slice image. In this way, the electronic device can determine the first fitting result corresponding to the intersection area change trend until the difference between each two adjacent structural similarity values ​​is determined. Wherein, i and n are positive integers.

[0139] S20126. Determine the number of continuous monotonic intervals in the first fitting result as the intersection area characteristic parameter.

[0140] The electronic device can identify the number of continuous monotonic intervals in the first fitting result, and determine the number of continuous monotonic intervals as the intersection area characteristic parameter. The continuous monotonic interval can be an interval in which the intersection pixels between each two adjacent slice images monotonically increase from small to large, or can be an interval in which the intersection pixels between each two adjacent slice images monotonically decrease from large to small.

[0141] It should be noted that the intersection area change trend of the target area to be treated with a relatively regular external shape is generally a monotonically increasing trend from small to large, and then a monotonically decreasing trend from large to small, that is, it increases first and then decreases, and there are two continuous monotonic intervals in the corresponding first fitting result. If the number of continuous monotonic intervals in the first fitting result is greater, it can be indicated that the intersection area change trend is more complex, the external shape of the target area to be treated is more irregular, and more targets need to be deployed to achieve a better irradiation treatment effect. Therefore, after the electronic device in the embodiment of the present application accurately determines the intersection area characteristic parameter, it can accurately adjust the initial number of target points based on the intersection area characteristic parameter to accurately determine the maximum number of target points.

[0142] In one embodiment, in the above S2012, if the shape feature parameter is a relative position feature parameter, the embodiment of the present application provides an optional implementation method, including: S20127-S20129.

[0143] S20127. Determine a second fitting result corresponding to the slice area change trend based on the target area pixels in each slice image.

[0144] The target pixels in the slice image are the pixels occupied by the target area to be treated in the slice image. The number of target pixels in the slice image corresponding to a layer of target slices can represent the target area of ​​the layer of target slices.

[0145] In one possible manner, the electronic device may perform fitting based on the number of target area pixels of each slice image in the continuous multi-layer slice images to determine a second fitting result corresponding to the slice area change trend. For example, the electronic device may record the acquisition order of the continuous multi-layer target area slices from first to last through the horizontal axis of the two-dimensional rectangular coordinate system, and record the number of target area pixels of each slice image through the vertical axis of the two-dimensional rectangular coordinate system, thereby obtaining the second fitting result corresponding to the slice area change trend.

[0146] In another possible manner, the electronic device may subtract the number of target pixels in the k+1th slice image from the number of target pixels in the kth slice image to obtain the difference in the number of target pixels between the kth slice image and the k+1th slice image, that is, the difference in the target area between the kth target slice and the k+1th target slice. In this way, the electronic device can obtain the second fitting result corresponding to the slice area change trend until the difference in the number of target pixels between each two adjacent slice images is determined. Wherein, k is a positive integer.

[0147] S20128. When the second fitting result and the first fitting result meet a preset condition, determine the first consistency as a relative position feature parameter.

[0148] It should be understood that the method for determining the first fitting result can refer to the description in the above S20125 and will not be repeated here.

[0149] The preset conditions include that the number of continuous monotonic intervals is the same and the slice images corresponding to the continuous monotonic intervals are the same. The first consistency is used to indicate that the change trend of the intersection area is consistent with the change trend of the slice area.

[0150] It should be noted that if the intersection area change trend is consistent with the slice area change trend, it can be indicated that the inter-layer difference of the target area to be treated is small and the shape of the target area to be treated is more regular. If the intersection area change trend is inconsistent with the slice area change trend, it can be indicated that the inter-layer difference of the target area to be treated is large and the shape of the target area to be treated is more irregular. If the intersection area change trend of adjacent layers of the target area to be treated shows a trend of increasing first and then decreasing, but the area change between the slices of each layer of the target area is not from small to large, then the inter-layer difference change is relatively large, and more targets need to be deployed to achieve a better irradiation treatment effect.

[0151] After the electronic device determines the second fitting result corresponding to the slice area change trend, it can determine the continuous monotonic interval in the second fitting result. Further, the electronic device can compare the continuous monotonic interval in the first fitting result with the continuous monotonic interval in the second fitting result to obtain a comparison result. If the comparison result is that the continuous monotonic interval in the first fitting result is consistent with the continuous monotonic interval in the second fitting result, it can be indicated that the shape of the target area to be treated is relatively regular. The electronic device determines that the second fitting result and the first fitting result meet the preset conditions, and determines the first consistency as the relative position characteristic parameter.

[0152] In this case, the value of the first consistency can be small so as not to constitute an adjustment to the initial number of target points. For example, the first consistency can be 0 or 0.1.

[0153] S20129: When the second fitting result and the first fitting result do not meet a preset condition, determine the second consistency as a relative position feature parameter.

[0154] The second consistency is used to indicate that the intersection area change trend and the slice area change trend are inconsistent.

[0155] If the comparison result shows that the continuous monotonic interval in the first fitting result is inconsistent with the continuous monotonic interval in the second fitting result, it can be indicated that the shape of the target area to be treated is relatively irregular. The electronic device determines that the second fitting result and the first fitting result do not meet the preset condition, and determines the second consistency as the relative position characteristic parameter.

[0156] In this case, the value of the second consistency can be larger to accurately adjust the initial number of target points. For example, the first consistency can be 1 or 2.

[0157] Based on this, after the electronic device in the embodiment of the present application accurately determines the relative position characteristic parameters, the initial number of target points can be accurately adjusted based on the relative position characteristic parameters to accurately determine the maximum number of target points.

[0158] In one embodiment, combining Figure 3The method for determining the number of targets shown in Figure 6 As shown, it is a flow chart of another method for determining the number of target points provided by an embodiment of the present application. In the above S203, when the electronic device determines the number of target points in the target area to be treated based on the initial number of target points and the shape characteristic parameters, the embodiment of the present application provides an optional implementation method, including: S2031-S2032.

[0159] S2031. Determine the number of characteristic target points based on the initial number of target points and shape characteristic parameters.

[0160] Among them, the number of characteristic target points includes at least one of the following: the first number of target points determined according to the initial number of target points, the hole characteristic parameter and the first coefficient, the second number of target points determined according to the intersection area characteristic parameter and the second coefficient, and the third number of target points determined according to the initial number of target points, the relative position characteristic parameter and the third coefficient.

[0161] In one possible manner, when the electronic device determines the first target point quantity according to the initial target point quantity, the hole characteristic parameter and the first coefficient, the initial target point quantity, the hole characteristic parameter and the first coefficient may be multiplied to obtain the first target point quantity. Alternatively, the electronic device may divide the product between the initial target point quantity and the hole characteristic parameter by the first coefficient to obtain the first target point quantity. For example, the first coefficient may be 3 or 0.4.

[0162] In another possible manner, when the electronic device determines the number of second target points according to the intersection area characteristic parameter and the second coefficient, the intersection area characteristic parameter may be divided by the second coefficient to obtain the number of second target points. Alternatively, the electronic device may multiply the intersection area characteristic parameter and the second coefficient to obtain the number of second target points. For example, the second coefficient may be 2 or 0.5.

[0163] In another possible manner, when the electronic device determines the third number of target points according to the initial number of target points, the relative position characteristic parameter and the third coefficient, the product of the relative position characteristic parameter, the initial number of target points and the third coefficient can be determined as the third number of target points. Alternatively, the electronic device can first divide the initial number of target points by the relative position characteristic parameter, and then further divide it by the third coefficient to obtain the third number of target points. The third coefficient can be 0.25 or 4.

[0164] S2032. Determine the number of target targets based on the number of initial targets and the number of characteristic targets.

[0165] In one possible manner, the electronic device may add the initial number of targets and the characteristic number of targets to obtain the target number of targets. The characteristic number of targets may be at least one of the first number of targets, the second number of targets, and the third number of targets. For example, when the characteristic number of targets is the first number of targets and the second number of targets, the electronic device may add the initial number of targets, the first number of targets, and the second number of targets to obtain the target number of targets. For another example, when the characteristic number of targets is the first number of targets, the second number of targets, and the third number of targets, the electronic device may add the initial number of targets, the first number of targets, the second number of targets, and the third number of targets to obtain the target number of targets.

[0166] In the embodiment of the present application, the electronic device can obtain the volume of the target area to be treated, and determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated. Since the initial number of target points is the number of a group of one or more collimators, and the combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. Therefore, the initial number of target points determined by the electronic device in the embodiment of the present application can accurately match the volume of the target area to be treated.

[0167] In addition, the electronic device can obtain the shape characteristic parameters of the target area to be treated, and further determine the maximum number of targets allowed to be deployed in the target area to be treated based on the initial number of target points and the shape characteristic parameters. Since the shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated, and the number of target targets is positively correlated with the shape characteristic parameters. Therefore, in the embodiment of the present application, the electronic device can determine the number of target targets based on the initial number of target points that matches the volume of the target area to be treated, combined with the complexity of the shape of the target area to be treated, so that the number of target targets can accurately match the volume and shape characteristics of the target area to be treated, can adapt to the uneven target phenomenon caused by the complex shape of the target area to be treated, and has higher rationality.

[0168] Based on this, compared with the method of giving the maximum number of targets based on manual experience, the number of target targets determined by this application can support automatic planning, without missing the optimal number of targets, to optimize the treatment plan based on a smaller maximum number of targets as much as possible, thereby improving the efficiency of finding the optimal number of targets. In summary, this application can be used to reasonably and accurately determine the maximum number of targets, and can support the efficient and accurate optimization of treatment plans.

[0169] The embodiment of the present application can divide the functional modules of the electronic device etc. according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0170] In the case of dividing each functional module into corresponding functional modules, Figure 7 FIG. 3 is a schematic diagram showing the structure of a device for determining the number of target points. The device 30 for determining the number of target points can be applied to electronic devices to implement any possible method involved in the above embodiments. Figure 7 As shown, the target point quantity determination device 30 may include: an acquisition unit 301 and a processing unit 302 .

[0171] The acquisition unit 301 is used to acquire the volume of the target area to be treated and the shape characteristic parameters. The shape characteristic parameters are used to reflect the complexity of the shape of the target area to be treated. The processing unit 302 is used to determine the initial number of target points in the target area to be treated according to the volume of the target area to be treated. The initial number of target points is the number of a group of one or more collimators. The combination of a group of one or more beam focal spot volumes corresponding to a group of one or more collimators matches the volume of the target area to be treated. The processing unit 302 is also used to determine the number of target target points in the target area to be treated based on the initial number of target points and the shape characteristic parameters. The number of target target points is positively correlated with the shape characteristic parameters. The number of target target points is used to indicate the maximum number of targets allowed to be deployed in the target area to be treated.

[0172] In some embodiments, the processing unit 302 is specifically configured to: obtain multiple beam focal spot volumes corresponding to collimators of different sizes, and determine the number of initial target points based on the volume of the target area to be treated and the multiple beam focal spot volumes.

[0173] In some embodiments, the processing unit 302 is specifically configured to: determine the number of collimators corresponding to the current beam focal spot volume that can be accommodated in the current remaining volume of the target area to be treated in order from large to small of the multiple beam focal spot volumes, and obtain the number of collimators of different sizes. The sum of the numbers of collimators of different sizes is determined as the initial target point number.

[0174] In some embodiments, the shape characteristic parameters include at least one of the following: a hole characteristic parameter of the target area to be treated, an intersection area characteristic parameter between continuous multi-layer target area slices of the target area to be treated, and a relative position characteristic parameter between continuous multi-layer target area slices. The hole characteristic parameter is positively correlated with the number of holes existing in the target area to be treated. The intersection area characteristic parameter is positively correlated with the number of direction changes of the intersection area change trend between continuous multi-layer target area slices, and the intersection area change trend is the size change trend of the intersection area between each two adjacent layers of target area slices. The relative position characteristic parameter is the consistency of the area change trend corresponding to the continuous multi-layer target area slices. The area change trend consistency is used to indicate whether the intersection area change trend and the slice area change trend are consistent. The slice area change trend is the size change trend of the slice area between each two adjacent layers of target area slices.

[0175] In some embodiments, the acquisition unit 301 is specifically used to: acquire slice images of each of the continuous multi-layer target area slices of the target area to be treated, and determine the shape feature parameters based on the slice images of each of the continuous multi-layer target area slices.

[0176] In some embodiments, the acquisition unit 301 is specifically used to: determine whether each layer of target area slice has holes based on the target area edge contour in each layer of slice image. In the case that there are target area slices with holes in the continuous multi-layer target area slices, the target irregularity is determined from the irregularities of the continuous multi-layer target area slices as the hole feature parameter. The greater the irregularity of the target area slice, the greater the probability of being determined as the target irregularity. The irregularity of each layer of target area slice is determined based on the valid rows, valid columns, target rows and target columns in the slice image of each layer of target area slice. The valid row is used to indicate the row where there are pixels located on the target area edge contour in the whole row of pixels. The valid column is used to indicate the column where there are pixels located on the target area edge contour in the whole column of pixels. The target row is used to indicate the row where the number of pixels located on the target area edge contour in the whole row of pixels is greater than the preset number. The target column is used to indicate the column where the number of pixels located on the target area edge contour in the whole column of pixels is greater than the preset number. In the case that there are no target area slices with holes in the continuous multi-layer target area slices, the preset value is determined as the hole feature parameter.

[0177] In some embodiments, the acquisition unit 301 is specifically configured to: determine that the target area slice has holes when the ratio of the target rows in the valid rows is greater than a preset ratio, or the ratio of the target columns in the valid columns is greater than a preset ratio. Determine that the target area slice does not have holes when the ratio of the target rows in the valid rows is less than or equal to the preset ratio, and the ratio of the target columns in the valid columns is less than or equal to the preset ratio.

[0178] In some embodiments, the irregularity of each target slice is the ratio of the sum of the number of target rows and the number of target columns to the sum of the number of valid rows and the number of valid columns.

[0179] In some embodiments, the acquisition unit 301 is specifically used to: determine the intersection pixels between each two adjacent slice images in the continuous multi-layer slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice. Based on the intersection pixels between each two adjacent slice images, a first fitting result corresponding to the intersection area change trend is determined. The number of continuous monotonic intervals in the first fitting result is determined as the intersection area characteristic parameter.

[0180] In some embodiments, the acquisition unit 301 is specifically used to: determine the second fitting result corresponding to the slice area change trend based on the target area pixels in each layer of slice image. When the second fitting result and the first fitting result meet the preset conditions, the first consistency is determined as the relative position feature parameter. The first fitting result is determined based on the intersection pixels between each two adjacent slice images. The intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice. The preset conditions include that the number of continuous monotonic intervals is the same and the slice images corresponding to the continuous monotonic intervals are the same. The first consistency is used to indicate that the intersection area change trend is consistent with the slice area change trend. When the second fitting result and the first fitting result do not meet the preset conditions, the second consistency is determined as the relative position feature parameter. The second consistency is used to indicate that the intersection area change trend is inconsistent with the slice area change trend.

[0181] In some embodiments, the processing unit 302 is specifically configured to: determine the number of characteristic target points based on the initial number of target points and the shape characteristic parameters. The number of characteristic target points includes at least one of the following: the number of first target points determined according to the initial number of target points, the hole characteristic parameter and the first coefficient, the number of second target points determined according to the intersection area characteristic parameter and the second coefficient, and the number of third target points determined according to the initial number of target points, the relative position characteristic parameter and the third coefficient. The number of target targets is determined according to the initial number of target points and the number of characteristic target points.

[0182] In the case of an integrated unit, Figure 8 FIG. 4 is a schematic diagram showing the structure of another target point number determination device. The target point number determination device 40 can be applied to an electronic device to implement any possible method involved in the above embodiments. Figure 8 As shown, the target point number determination device 40 may include: a processing module 401 and a communication module 402. The processing module 401 may be used to control and manage the actions of the target point number determination device 40. The communication module 402 may be used to support the communication between the target point number determination device 40 and other entities. Figure 8 As shown, the target point quantity determination device 40 may further include a storage module 403 for storing program codes and data of the target point quantity determination device 40 .

[0183] The processing module 401 may be a processor or a controller. The communication module 402 may be a transceiver, a transceiver circuit or a communication interface, etc. The storage module 403 may be a memory.

[0184] When the processing module 401 is a processor, the communication module 402 is a transceiver, and the storage module 403 is a memory, the processor, the transceiver, and the memory may be connected via a bus.

[0185] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0186] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0187] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0188] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0189] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing a computer program instruction on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0190] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for determining the number of target points, characterized in that: include: Obtaining the volume and shape characteristic parameters of the target area to be treated; The shape characteristic parameter is used to reflect the complexity of the shape of the target area to be treated; Determining the initial number of target points in the target area to be treated according to the volume of the target area to be treated; The number of initial target points is the number of a group of one or more collimators; a combination of a group of one or more beam focal spot volumes corresponding to the group of one or more collimators matches the volume of the target area to be treated; Determining the number of target targets in the target area to be treated based on the number of initial target points and the shape characteristic parameters; the number of target targets is positively correlated with the shape characteristic parameters; The target target number is used to indicate the maximum number of targets allowed to be deployed in the target area to be treated.

2. The method according to claim 1, characterized in that Determining the initial number of target points in the target area to be treated according to the volume of the target area to be treated includes: Acquire a plurality of beam focal spot volumes corresponding to collimators of different sizes; The initial number of target points is determined based on the volume of the target area to be treated and the multiple beam focal spot volumes.

3. The method according to claim 2, characterized in that The step of determining the number of initial target points based on the volume of the target area to be treated and the multiple beam focal spot volumes comprises: Determining the number of collimators corresponding to the current beam focal spot volume that can be accommodated in the current remaining volume of the target area to be treated in order from large to small of the multiple beam focal spot volumes, and obtaining the number of collimators of different sizes; The sum of the numbers of the collimators of different sizes is determined as the number of initial target points.

4. The method according to claim 1, characterized in that: The shape characteristic parameter includes at least one of the following: a hole characteristic parameter of the target area to be treated, an intersection area characteristic parameter between continuous multi-layer target area slices of the target area to be treated, and a relative position characteristic parameter between the continuous multi-layer target area slices; the hole characteristic parameter is positively correlated with the number of holes existing in the target area to be treated; the intersection area characteristic parameter is positively correlated with the number of direction changes of the intersection area change trend between the continuous multi-layer target area slices, and the intersection area change trend is the size change trend of the intersection area between each two adjacent layers of target area slices; the relative position characteristic parameter is the area change trend consistency corresponding to the continuous multi-layer target area slices; the area change trend consistency is used to indicate whether the intersection area change trend is consistent with the slice area change trend; The slice area variation trend is the slice area variation trend between each two adjacent target slices.

5. The method according to claim 4, characterized in that Obtaining shape characteristic parameters of the target area to be treated includes: Acquire slice images of each of the continuous multi-layer target area slices of the target area to be treated; The shape characteristic parameters are determined based on the slice images of each of the continuous multi-layer target area slices.

6. The method according to claim 5, characterized in that In the case where the shape characteristic parameters include the hole characteristic parameters, determining the shape characteristic parameters based on the slice images of each of the continuous multi-layer target area slices includes: Based on the target area edge contour in each slice image, determine whether each target area slice has holes; In the case that there are target area slices with holes in the continuous multi-layer target area slices, the target irregularity is determined from the respective irregularities of the continuous multi-layer target area slices as the hole feature parameter; the greater the irregularity of the target area slice, the greater the probability of being determined as the target irregularity; the irregularity of each layer of target area slices is determined based on the valid rows, valid columns, target rows and target columns in the slice image of each layer of target area slices; the valid rows are used to indicate the rows in which there are pixels located on the edge contour of the target area in the entire row of pixels; the valid columns are used to indicate the columns in which there are pixels located on the edge contour of the target area in the entire column of pixels; the target rows are used to indicate the rows in which the number of pixels located on the edge contour of the target area in the entire row of pixels is greater than a preset number; the target columns are used to indicate the columns in which the number of pixels located on the edge contour of the target area in the entire column of pixels is greater than a preset number; When there is no target area slice with a hole in the continuous multi-layer target area slices, a preset value is determined as the hole characteristic parameter.

7. The method according to claim 6, characterized in that The step of determining whether each target area slice has holes based on the target area edge contour in each slice image comprises: When the ratio of the target rows in the valid rows is greater than a preset ratio, or the ratio of the target columns in the valid columns is greater than the preset ratio, determining that the target area slice has holes; When the ratio of the target rows in the valid rows is less than or equal to the preset ratio, and the ratio of the target columns in the valid columns is less than or equal to the preset ratio, it is determined that the target area slice has no holes.

8. The method according to claim 6, characterized in that The irregularity of each target area slice is the ratio of the sum of the number of target rows and the number of target columns to the sum of the number of valid rows and the number of valid columns.

9. The method according to claim 5, characterized in that In the case where the shape characteristic parameters include the intersection area characteristic parameters, determining the shape characteristic parameters based on the slice images of each of the continuous multi-layer target area slices includes: Determine the intersection pixels between each two adjacent slice images in the continuous multi-layer slice images; the intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice; Determine a first fitting result corresponding to the intersection area variation trend based on the intersection pixels between each two adjacent slice images; The number of continuous monotonic intervals in the first fitting result is determined as the intersection area characteristic parameter.

10. The method according to claim 5, characterized in that In the case where the shape characteristic parameters include the relative position characteristic parameters, determining the shape characteristic parameters based on the slice images of each of the continuous multi-layer target area slices includes: Determine a second fitting result corresponding to the slice area variation trend based on target area pixels in each slice image; In the case where the second fitting result and the first fitting result meet the preset conditions, the first consistency is determined as the relative position characteristic parameter; the first fitting result is determined based on the intersection pixels between each two adjacent slice images; the intersection pixels are used to represent pixels with the same pixel position between the two slice images and located in the target slice; the preset conditions include the same number of continuous monotonic intervals and the same slice images corresponding to the continuous monotonic intervals; the first consistency is used to indicate that the intersection area change trend is consistent with the slice area change trend; When the second fitting result and the first fitting result do not meet the preset condition, a second consistency is determined as the relative position characteristic parameter; the second consistency is used to indicate that the intersection area change trend and the slice area change trend are inconsistent.

11. The method according to claim 4, characterized in that The step of determining the number of target points in the target area to be treated based on the number of initial target points and the shape characteristic parameters includes: Based on the initial number of target points and the shape characteristic parameters, the number of characteristic target points is determined; the number of characteristic target points includes at least one of the following: a first number of target points determined according to the initial number of target points, the hole characteristic parameters and a first coefficient, a second number of target points determined according to the intersection area characteristic parameters and a second coefficient, and a third number of target points determined according to the initial number of target points, the relative position characteristic parameters and a third coefficient; The number of target targets is determined according to the number of initial targets and the number of characteristic targets.

12. An electronic device, characterized in that: The electronic device comprises: processor; a memory configured to store instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1-11.

13. A non-volatile storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is read and executed, the method described in any one of claims 1 to 11 is implemented.

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