A method and apparatus for fetal cardiovascular physiology structure examination, and an ultrasonic device

Abstract

The application discloses a fetal cardiovascular physiological structure examination method and device, an ultrasonic equipment and a computer readable storage medium. The method comprises the following steps: determining a first measurement section and a first measurement item in the first measurement section of the fetal cardiovascular physiological structure examination; acquiring a gestation period parameter, determining a prediction model corresponding to the first measurement item and an evaluation model; wherein the gestation period parameter comprises any one or a combination of multiple of the following parameters: gestational age, biparietal diameter and femur long diameter; collecting the first measurement section, and determining an actual value of the first measurement item in the first measurement section; predicting a prediction value corresponding to the first measurement item based on the gestation period parameter by using the prediction model; calculating an evaluation value of the first measurement item based on the prediction value and the actual value by using the evaluation model, and obtaining an evaluation result of the first measurement item according to the evaluation value. The application meets the difference of different regions or different races, and improves the accuracy of the fetal cardiovascular physiological structure examination.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasound, more particularly, to a fetal cardiovascular physiological structure examination method and device, an ultrasound device and a computer readable storage medium. BACKGROUND

[0002] With the development of fetal echocardiography, dynamically evaluating fetal cardiovascular development during pregnancy, quantitatively analyzing and predicting the development outcome of the fetus in the later stage have become a hot and difficult point of research at home and abroad. At present, the most representative fetal heart physiological structure measurement parameter Z-score research is the Z-score model and reference range of fetal cardiovascular measurement published by C. SCHNEIDER et al. in 2005. The actual value of the measurement item is measured by the ultrasound device, and the Z-score score is calculated based on the above Z-score model, and compared with the preset reference range to obtain the examination result. However, due to racial differences and regional differences, the model and the Z-score normal reference range of each measurement item can only represent the fetuses in part of the region, and cannot represent fetuses of different races in all regions around the world.

[0003] Therefore, how to meet the differences of different regions or different races and improve the accuracy of fetal cardiovascular physiological structure examination is a technical problem to be solved by those skilled in the art. SUMMARY

[0004] The purpose of the present application is to provide a fetal cardiovascular physiological structure examination method and device, an ultrasound device and a computer readable storage medium, which meet the differences of different regions or different races and improve the accuracy of fetal cardiovascular physiological structure examination.

[0005] To achieve the above purpose, the present application provides a fetal cardiovascular physiological structure examination method, comprising:

[0006] determining a first measurement section of fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section;

[0007] obtaining a gestational parameter, determining a prediction model and an evaluation model corresponding to the first measurement item; wherein the gestational parameter includes any one or a combination of several of gestational age, biparietal diameter and femur long diameter;

[0008] collecting the first measurement section, and determining an actual value of the first measurement item in the first measurement section;

[0009] predicting a predicted value corresponding to the first measurement item based on the gestational parameter by using the prediction model;

[0010] An evaluation model is used to calculate an evaluation value of the first measurement item based on the predicted value and the actual value, and an evaluation result of the first measurement item is obtained according to the evaluation value.

[0011] Further comprising:

[0012] A second measurement section requiring a customized prediction model is determined, and a second measurement item in the second measurement section is determined.

[0013] The gestational parameter corresponding to a normal fetus is obtained, the second measurement section is collected, and a sample value of the second measurement item in the second measurement section is determined.

[0014] A customized prediction model corresponding to the second measurement item in the second measurement section is constructed based on the gestational parameter corresponding to a normal fetus and the corresponding sample value by using a statistical analysis tool.

[0015] The determination of the prediction model corresponding to the first measurement item comprises:

[0016] All candidate prediction models corresponding to the first measurement item are determined, wherein the candidate prediction models include default prediction models of an ultrasound device and customized prediction models.

[0017] The prediction model corresponding to the first measurement item is determined from all the candidate prediction models.

[0018] Before the determination of the prediction model and the evaluation model corresponding to the first measurement item, further comprising:

[0019] An imaging mode is determined.

[0020] Correspondingly, the determination of all candidate prediction models corresponding to the first measurement item comprises:

[0021] All candidate prediction models corresponding to the first measurement item in the imaging mode are determined.

[0022] The evaluation model comprises a Z-score evaluation model, and the calculation of the evaluation value of the first measurement item by using the evaluation model based on the predicted value and the actual value comprises:

[0023] The Z-score of the first measurement item is calculated based on the predicted value and the actual value by using the Z-score evaluation model.

[0024] The evaluation result of the first measurement item according to the evaluation value comprises:

[0025] determining a normal evaluation value range corresponding to the first measurement item, and determining fetal abnormality if the evaluation value of the first measurement item exceeds the normal evaluation value range.

[0026] wherein after obtaining the evaluation result of the first measurement item according to the evaluation value, the method further comprises:

[0027] writing the evaluation result of the first measurement item into a measurement report, wherein the measurement report comprises actual value, predicted value, evaluation value and normal evaluation value range corresponding to the first measurement item.

[0028] To achieve the above object, the present application provides a fetal cardiovascular physiological structure examination device, comprising:

[0029] a first determination module configured to determine a first measurement section of fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section;

[0030] a second determination module configured to obtain a gestation period parameter, determine a prediction model and an evaluation model corresponding to the first measurement item, wherein the gestation period parameter comprises any one or a combination of several of gestational age, biparietal diameter and femur long diameter;

[0031] a first acquisition module configured to acquire the first measurement section and determine actual value of the first measurement item in the first measurement section;

[0032] a prediction module configured to predict a predicted value corresponding to the first measurement item based on the gestation period parameter by using the prediction model;

[0033] an evaluation module configured to calculate an evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, and obtain an evaluation result of the first measurement item according to the evaluation value.

[0034] To achieve the above object, the present application provides an ultrasonic device, comprising:

[0035] a memory configured to store a computer program;

[0036] a processor configured to execute the computer program to realize the steps of the fetal cardiovascular physiological structure examination method.

[0037] To achieve the above object, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps of the fetal cardiovascular physiological structure examination method.

[0038] It can be known from the above scheme that the fetal cardiovascular physiological structure examination method provided in the application comprises the following steps: determining a first measurement section of fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section; obtaining a gestation period parameter, determining a prediction model corresponding to the first measurement item and an evaluation model; wherein the gestation period parameter comprises any one or a combination of several of gestational weeks, biparietal diameter and femur long diameter; collecting the first measurement section, and determining an actual value of the first measurement item in the first measurement section; predicting a predicted value corresponding to the first measurement item based on the gestation period parameter by using the prediction model; calculating an evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, and obtaining an evaluation result of the first measurement item according to the evaluation value.

[0039] In the application, a plurality of prediction models and evaluation models are included in the ultrasound device, which correspond to different regions and different races respectively. When performing fetal cardiovascular physiological structure examination, the corresponding prediction model and evaluation model can be selected according to the region where the fetus is located and the race to which the fetus belongs, so as to meet the difference of different regions or different races, the predicted value of the measurement item is determined based on the prediction model, and the evaluation result of the measurement item can be obtained based on the actual value and the predicted value of the measurement item by using the evaluation model, thereby improving the accuracy of fetal cardiovascular physiological structure examination. The application also discloses a fetal cardiovascular physiological structure examination device, an ultrasound device and a computer readable storage medium, which can also achieve the above technical effects.

[0040] It should be understood that the foregoing general description and the following detailed description are only exemplary and cannot limit the application. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor. The drawings are used to provide further understanding of the disclosure and constitute a part of the specification, and are used to explain the disclosure together with the following specific embodiments, but do not constitute a limitation on the disclosure. In the drawings:

[0042] Figure 1 A flow chart of a fetal cardiovascular physiological structure examination method according to an exemplary embodiment is shown;

[0043] Figure 2 A flow chart of another fetal cardiovascular physiological structure examination method according to an exemplary embodiment is shown;

[0044] Figure 3 FIG. 1 is a structural diagram of a fetal cardiovascular physiological structure examination device according to an example embodiment;

[0045] Figure 4 FIG. 2 is a structural diagram of an ultrasound device according to an example embodiment. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application. In addition, in the embodiments of the present application, "first", "second", and the like are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence.

[0047] The embodiments of the present application disclose a fetal cardiovascular physiological structure examination method, which meets the difference of different regions or different races and improves the accuracy of fetal cardiovascular physiological structure examination.

[0048] Referring to Figure 1 FIG. 3 is a flowchart of a fetal cardiovascular physiological structure examination method according to an example embodiment, as shown in Figure 1 includes the following steps.

[0049] S101: determining a first measurement section of fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section;

[0050] The execution subject of the embodiment is an ultrasound device, which contains various prediction models and evaluation models, which can be built-in when the ultrasound device is manufactured, or can be imported by the user for customization. The process of customizing the prediction model will be introduced in the next embodiment.

[0051] In a specific implementation, the user selects the measurement section of fetal cardiovascular physiological structure examination and the measurement item under the measurement section in the ultrasound device. The measurement section can include a left ventricular long-axis section, an aortic arch section, a short-axis section, a right ventricular oblique short-axis section, and a four-chamber heart section, and the measurement item can include an aortic valve, an ascending aorta under the left ventricular long-axis section, an aortic valve, an ascending aorta, an inferior vena cava, a descending aorta under the aortic arch section, a pulmonary valve, a main pulmonary artery, a left pulmonary artery, a right pulmonary artery under the short-axis section, a ductus arteriosus under the right ventricular oblique short-axis section, a tricuspid valve, a right ventricular end-diastolic internal diameter, a right ventricular long diameter, a right ventricular area, a mitral valve, a left ventricular end-diastolic internal diameter, a left ventricular long diameter, and a left ventricular area under the four-chamber heart section.

[0052] S102: Obtain a gestation parameter, and determine a prediction model and an evaluation model corresponding to the first measurement item; wherein the gestation parameter comprises any one or a combination of a plurality of the following: gestational age, biparietal diameter, and femur length;

[0053] In this step, the user inputs gestation parameters such as gestational age (GA), biparietal diameter (BPD), and femur length (FL) in the ultrasound device, and selects a corresponding prediction model and evaluation model according to the measurement item, the region where the fetus is located, and the race to which the fetus belongs.

[0054] As a preferred implementation, the determination of the prediction model corresponding to the first measurement item comprises: determining all candidate prediction models corresponding to the first measurement item; wherein the candidate prediction models comprise default prediction models of the ultrasound device and custom prediction models; and determining the prediction model corresponding to the first measurement item from all the candidate prediction models. In a specific implementation, the user can select an imaging mode, and the ultrasound device displays all the candidate prediction models corresponding to the selected imaging mode and the measurement item, including default prediction models of the ultrasound device, i.e., prediction models built in the ultrasound device when it is shipped, and custom prediction models of the user, from which the user can select a corresponding prediction model according to the region where the fetus is located and the race to which the fetus belongs.

[0055] S103: Collect the first measurement section, and determine an actual value of the first measurement item in the first measurement section.

[0056] In this step, the ultrasound device collects a measurement section under the imaging mode selected by the user, and determines an actual value of the measurement item in the measurement section.

[0057] S104: Predict a prediction value corresponding to the first measurement item based on the gestation parameter by using the prediction model.

[0058] In this step, the prediction model is used to predict the measurement item selected by the user based on the gestation parameter. The prediction model can be understood as a mapping relationship between the gestation parameter and the prediction value, and the prediction value of the measurement item can be understood as a standard value of the measurement item under the input gestation parameter.

[0059] S105: Calculate an evaluation value of the first measurement item based on the prediction value and the actual value by using the evaluation model, and obtain an evaluation result of the first measurement item according to the evaluation value.

[0060] In this step, an evaluation model is used to calculate an evaluation value of the measurement item, the evaluation value is used to evaluate the difference between the actual value and the predicted value of the measurement item, and the evaluation result of the measurement item can be obtained according to the evaluation value. In a specific implementation, it is necessary to determine the normal evaluation value range corresponding to the measurement item, if the evaluation value of the measurement item exceeds the normal evaluation value range, it is determined that the fetus is abnormal, and if the evaluation value is within the normal evaluation value range, it is determined that the fetus is normal.

[0061] Preferably, the evaluation model includes a Z-score evaluation model, and the evaluation value of the first measurement item is calculated based on the predicted value and the actual value by using the evaluation model, including: calculating the Z-score of the first measurement item based on the predicted value and the actual value by using the Z-score evaluation model. Z-score is a process of standardization by applying random variable theory (population) mean and standard deviation, and the relationship between Z-score, mean and standard deviation can be: Z-score=(x-μ) / σ, wherein x is the actual value of the measurement item, μ is the predicted value of the measurement item, and σ is the standard deviation.

[0062] It should be noted that the evaluation model includes two aspects, one is the calculation method of the evaluation value of the measurement item, and the other is the normal evaluation value range of the measurement item. Any difference in either aspect is a different evaluation model, that is, users can select different evaluation models, select different evaluation value calculation methods, and select different normal evaluation value ranges to meet the differences of different regions or different races.

[0063] As a preferred mode, the step further includes: writing the evaluation result of the first measurement item into a measurement report; wherein the measurement report includes the actual value, the predicted value, the evaluation value and the normal evaluation value range corresponding to the first measurement item. In a specific implementation, a measurement report of the measurement item can be generated based on the evaluation result, and the measurement report can include the actual value, the predicted value, the evaluation value and the normal evaluation value range of the measurement item.

[0064] In the embodiments of the present application, the ultrasonic device includes a plurality of prediction models and evaluation models corresponding to different regions and different races. When performing fetal cardiovascular physiological structure examination, the corresponding prediction model and evaluation model can be selected according to the region where the fetus is located and the race to which the fetus belongs, so as to meet the differences of different regions or different races, determine the predicted value of the measurement item based on the prediction model, and obtain the evaluation result of the measurement item based on the actual value and the predicted value of the measurement item by using the evaluation model, thereby improving the accuracy of fetal cardiovascular physiological structure examination.

[0065] This embodiment introduces the process of customizing a prediction model, and specifically:

[0066] Referring to Figure 2 , a flow chart of another method for checking a fetal cardiovascular physiological structure according to an example embodiment, as shown in FIG. 14, includes: Figure 2

[0067] S201: determining a second measurement section for which a prediction model needs to be customized and a second measurement item in the second measurement section;

[0068] In the embodiment, the user selects, in the ultrasound device, a measurement section for which a prediction model needs to be customized and a measurement item under the measurement section, which is different from the previous embodiment in that the embodiment does not need to select a prediction model and an evaluation model corresponding to the measurement item, but customizes the prediction model in the following steps. That is, in the previous embodiment, the ultrasound device is used for checking a fetal cardiovascular physiological structure, and in the embodiment, the ultrasound device is used for customizing a prediction model.

[0069] It can be understood that the user can select a corresponding measurement item according to the content concerned by the medical institution, and then build a corresponding customized prediction model, thereby realizing the expansion of the measurement items for checking a fetal cardiovascular physiological structure.

[0070] S202: obtaining a gestational parameter corresponding to a normal fetus, collecting the second measurement section, and determining a sample value of the second measurement item in the second measurement section;

[0071] The purpose of the step is to collect a large number of sample values of the measurement item, and the specific collection process is similar to that of S103 in the previous embodiment. The user inputs a gestational parameter in the ultrasound device, collects a measurement section selected by the user, and determines a sample value of the second measurement item in the measurement section. The difference from S103 is that after the sample value of the measurement item of the fetus is collected, the user needs to make an abnormality judgment on the fetus, and only the sample value corresponding to the normal fetus is retained.

[0072] Since the checking of a fetal cardiovascular physiological structure and the customization of a prediction model both need to collect measurement items, in the embodiment, the user can also input information such as the last menstrual period, the number of fetuses, and the information of the checking doctor, and the ultrasound device can filter the checking by the checking time, the checking doctor, and the number of fetuses, determine the data collected in the process of defining the prediction model, and generate a corresponding relationship between the gestational parameter and the measurement item. It can be understood that if a plurality of prediction models corresponding to measurement items need to be customized, a plurality of measurement items can be collected from one sample (i.e., a normal fetus) at the same time, a corresponding relationship between a gestational parameter and sample values of a plurality of measurement items is constructed, the construction efficiency of the prediction model is improved, and further, the above corresponding relationship can be exported in the form of a data table, thereby reducing the workload of data arrangement.

[0073] ​S203: constructing a self-defined prediction model corresponding to the second measurement item in the second measurement section based on the normal fetus corresponding gestational parameter and the corresponding sample value by using a statistical analysis tool.

[0074] In this step, the sample value of the measurement item corresponding to the gestational parameter of the normal fetus is imported into the statistical analysis tool to generate the prediction model corresponding to the measurement item. The statistical analysis tool here can be a statistical analysis tool built-in the ultrasound device, or the sample value of the measurement item corresponding to the gestational parameter of the normal fetus can be exported from the ultrasound device, and the statistical analysis tool is analyzed offline to obtain the prediction model and then imported into the ultrasound device.

[0075] It can be seen that the ultrasound device of the embodiment obtains a large number of sample values of the measurement item corresponding to different gestational parameters, which is used to construct a self-defined model of the measurement item, so that it is suitable for fetuses of different regions or different races, and is suitable for the content concerned by different medical institutions, thereby improving the applicability of the fetal cardiovascular physiological structure examination.

[0076] Next, a fetal cardiovascular physiological structure examination device provided by the embodiment of the present application is introduced, and the fetal cardiovascular physiological structure examination device described below can be referred to the fetal cardiovascular physiological structure examination method described above.

[0077] Referring to Figure 3 , a structure diagram of a fetal cardiovascular physiological structure examination device according to an exemplary embodiment is shown, as Figure 3 shown, comprising:

[0078] The first determination module 301 is configured to determine a first measurement section of the fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section.

[0079] The second determination module 302 is configured to obtain a gestational parameter, determine a prediction model and an evaluation model corresponding to the first measurement item; wherein the gestational parameter includes any one or a combination of any several of gestational weeks, biparietal diameter and femur long diameter.

[0080] The first acquisition module 303 is configured to acquire the first measurement section, and determine an actual value of the first measurement item in the first measurement section.

[0081] The prediction module 304 is configured to predict a predicted value corresponding to the first measurement item based on the gestational parameter by using the prediction model.

[0082] The evaluation module 305 is configured to calculate an evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, and obtain an evaluation result of the first measurement item according to the evaluation value.

[0083] In the embodiment of the present application, the ultrasonic device includes a plurality of prediction models and evaluation models corresponding to different regions and different races. When performing the fetal cardiovascular physiological structure examination, the corresponding prediction model and evaluation model can be selected according to the region where the fetus is located and the race to which the fetus belongs, so as to meet the difference of different regions or different races, the prediction value of the measurement item is determined based on the prediction model, and the evaluation result of the measurement item is obtained based on the actual value and the prediction value of the measurement item by using the evaluation model, thereby improving the accuracy of the fetal cardiovascular physiological structure examination.

[0084] On the basis of the above-mentioned embodiment, as a preferred implementation manner, further comprising:

[0085] The third determination module is configured to determine a second measurement section requiring a self-defined prediction model and a second measurement item in the second measurement section.

[0086] The second acquisition module is configured to acquire the gestational parameter corresponding to the normal fetus, acquire the second measurement section, and determine a sample value of the second measurement item in the second measurement section.

[0087] The construction module is configured to construct the self-defined prediction model corresponding to the second measurement item in the second measurement section by using a statistical analysis tool based on the gestational parameter corresponding to the normal fetus and the corresponding sample value.

[0088] On the basis of the above-mentioned embodiment, as a preferred implementation manner, the first determination module 302 comprises:

[0089] The acquisition unit is configured to acquire the gestational parameter.

[0090] The first determination unit is configured to determine all candidate prediction models corresponding to the first measurement item; wherein the candidate prediction models include a default prediction model of the ultrasonic device and a self-defined prediction model.

[0091] The second determination unit is configured to determine the prediction model corresponding to the first measurement item from all the candidate prediction models.

[0092] On the basis of the above-mentioned embodiment, as a preferred implementation manner, further comprising:

[0093] The fourth determination module is configured to determine an imaging mode.

[0094] Correspondingly, the first determination unit is specifically a unit for determining all candidate prediction models corresponding to the first measurement item in the imaging mode.

[0095] On the basis of the above-mentioned embodiments, as a preferred implementation, the evaluation module 305 is specifically a module that calculates the Z-score of the first measurement item based on the predicted value and the actual value by using the Z-score evaluation model, and obtains the evaluation result of the first measurement item according to the Z-score.

[0096] On the basis of the above-mentioned embodiments, as a preferred implementation, the evaluation module 305 is specifically a module that calculates the evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, determines the normal evaluation value range corresponding to the first measurement item, and determines fetal abnormalities if the evaluation value of the first measurement item exceeds the normal evaluation value range.

[0097] On the basis of the above-mentioned embodiments, as a preferred implementation, the method further comprises:

[0098] a writing module configured to write the evaluation result of the first measurement item into a measurement report; wherein the measurement report comprises the actual value, the predicted value, the evaluation value and the normal evaluation value range corresponding to the first measurement item.

[0099] As to the device in the above-mentioned embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the method, and will not be described in detail here.

[0100] Based on the hardware implementation of the above-mentioned program modules, and in order to implement the method of the embodiments of the present application, the embodiments of the present application also provide an ultrasonic device, Figure 4 As shown in FIG. 1, the ultrasonic device includes: Figure 4

[0101] a communication interface 1 capable of information interaction with other devices such as network devices and the like;

[0102] a processor 2 connected with the communication interface 1 to realize information interaction with other devices, for running a computer program, and executing the fetal cardiovascular physiological structure examination method provided by one or more technical solutions described above. The computer program is stored on a memory 3.

[0103] Of course, in actual application, each component in the ultrasonic device is coupled together through a bus system 4. It can be understood that the bus system 4 is used to realize the connection and communication between the components. In addition to the data bus, the bus system 4 also includes a power bus, a control bus and a state signal bus. However, for the purpose of clear illustration, all kinds of buses are marked as the bus system 4 in Figure 4 .

[0104] ​The memory 3 in the embodiments of the present application is used to store various types of data to support the operation of the ultrasound device. Examples of these data include: any computer programs for operating on the ultrasound device.

[0105] It can be understood that the memory 3 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM). The magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example but not limitation, many forms of RAM can be used, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), sync link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memory 3 described in the embodiments of the present application is intended to include, but not limited to, these and any other suitable types of memory.

[0106] The method disclosed in the embodiments of the present application can be applied in the processor 2 or implemented by the processor 2. The processor 2 can be an integrated circuit chip with processing capability. In the implementation process, each step of the above method can be completed by the integrated logic circuit of hardware in the processor 2 or the instruction in the form of software. The processor 2 described above can be a general processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The processor 2 can implement or execute the disclosed methods, steps and logic block diagrams in the embodiments of the present application. The general processor can be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiments of the present application, the execution can be directly embodied as hardware decoding processor or executed by the combination of hardware and software modules in the decoding processor. The software module can be located in the storage medium, which is located in the memory 3. The processor 2 reads the program in the memory 3 and combines the hardware to complete the steps of the above method.

[0107] The processor 2 implements the corresponding flow in each method of the embodiments of the present application when executing the program. For brevity, it will not be repeated here.

[0108] In the exemplary embodiments, the embodiments of the present application also provide a storage medium, i.e. a computer storage medium, specifically a computer readable storage medium, such as a memory 3 storing a computer program, which can be executed by the processor 2 to complete the steps of the above method. The computer readable storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM, etc.

[0109] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by program instruction related hardware, and the above program can be stored in a computer readable storage medium. When the program is executed, the steps of the above method embodiments are executed. The storage medium includes mobile storage device, ROM, RAM, magnetic disc or optical disc, and various media that can store program codes.

[0110] Alternatively, the above-mentioned integrated units of the present application, if realized in the form of software function modules and sold or used as independent products, can also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions for causing an ultrasonic device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: mobile storage devices, ROM, RAM, magnetic disks or optical disks, and various media that can store program codes.

[0111] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of fetal cardiovascular physiologic structure examination, performed by an ultrasound device, characterized in that, The method comprises the following steps: determining a first measurement section of a fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section; obtaining a gestational age parameter, determining a prediction model and an evaluation model corresponding to the first measurement item from a plurality of prediction models and a plurality of evaluation models in an ultrasound device; wherein the gestational age parameter comprises any one or a combination of a plurality of items including gestational age, biparietal diameter and femur length; collecting the first measurement section and determining an actual value of the first measurement item in the first measurement section; predicting a predicted value corresponding to the first measurement item based on the gestational age parameter by using the prediction model; calculating an evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, and obtaining an evaluation result of the first measurement item according to the evaluation value; wherein the determination of the prediction model corresponding to the first measurement item comprises: determining all candidate prediction models corresponding to the first measurement item; wherein the candidate prediction models include default prediction models and self-defined prediction models of the ultrasound device; determining the prediction model corresponding to the first measurement item from all the candidate prediction models; wherein before the determination of the prediction model and the evaluation model corresponding to the first measurement item, the method further comprises: determining an imaging mode; correspondingly, the determination of all candidate prediction models corresponding to the first measurement item comprises: determining all candidate prediction models corresponding to the first measurement item under the imaging mode; wherein different candidate prediction models correspond to different regions and different ethnic groups; correspondingly, the determination of the prediction model corresponding to the first measurement item from all the candidate prediction models comprises: determining the prediction model corresponding to the first measurement item according to the region where the fetus is located and the ethnic group to which the fetus belongs from all the candidate prediction models.

2. The method of fetal cardiovascular physiologic structure examination according to claim 1, characterized in that, The method further comprises: determining a second measurement section and a second measurement item in the second measurement section which need a self-defined prediction model; obtaining a gestational age parameter corresponding to a normal fetus, collecting the second measurement section, and determining a sample value of the second measurement item in the second measurement section; constructing a self-defined prediction model corresponding to the second measurement item in the second measurement section by using a statistical analysis tool based on the gestational age parameter corresponding to the normal fetus and the corresponding sample value.

3. The method of fetal cardiovascular physiologic structure examination according to claim 1, characterized in that, The evaluation model comprises a Z-score evaluation model, and the calculation of the evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model comprises: calculating a Z-score of the first measurement item based on the predicted value and the actual value by using the Z-score evaluation model.

4. The method of fetal cardiovascular physiologic structure examination according to claim 1, characterized in that, The obtaining of the evaluation result of the first measurement item according to the evaluation value comprises: determining a normal evaluation value range corresponding to the first measurement item, and determining that the fetus is abnormal if the evaluation value of the first measurement item exceeds the normal evaluation value range.

5. The method of fetal cardiovascular physiologic structure examination according to claim 1, characterized in that, After the obtaining of the evaluation result of the first measurement item according to the evaluation value, the method further comprises: Write the evaluation result of the first measurement item into a measurement report; wherein the measurement report comprises the actual value, the predicted value, the evaluation value and the normal evaluation value range of the first measurement item.

6. An apparatus for fetal cardiovascular physiologic structure examination, characterized in that, The method comprises the steps of: The first determining module is configured to determine a first measurement section of a fetal cardiovascular physiological structure examination and a first measurement item in the first measurement section. The second determining module is configured to obtain a gestational period parameter, determine a prediction model and an evaluation model corresponding to the first measurement item from a plurality of prediction models and a plurality of evaluation models in an ultrasound device; wherein the gestational period parameter comprises any one or a combination of a plurality of items of gestational weeks, biparietal diameter and femur long diameter. The first acquisition module is configured to acquire the first measurement section and determine an actual value of the first measurement item in the first measurement section. The prediction module is configured to predict a predicted value corresponding to the first measurement item based on the gestational period parameter by using the prediction model. The evaluation module is configured to calculate an evaluation value of the first measurement item based on the predicted value and the actual value by using the evaluation model, and obtain an evaluation result of the first measurement item according to the evaluation value. The second determining module comprises: The acquisition unit is configured to obtain a gestational period parameter. The first determining unit is configured to determine all candidate prediction models corresponding to the first measurement item; wherein the candidate prediction models comprise a default prediction model and a self-defined prediction model of the ultrasound device. The second determining unit is configured to determine the prediction model corresponding to the first measurement item from all the candidate prediction models. The fourth determining module is configured to determine an imaging mode. Correspondingly, the first determining unit is specifically configured to determine all candidate prediction models corresponding to the first measurement item in the imaging mode; wherein different candidate prediction models correspond to different regions and different ethnic groups. Correspondingly, the second determining unit is specifically configured to determine the prediction model corresponding to the first measurement item from all the candidate prediction models according to the region where the fetus is located and the ethnic group to which the fetus belongs. The method comprises the steps of:

7. An ultrasound apparatus, characterized by The memory is configured to store a computer program. The processor is configured to implement the steps of the fetal cardiovascular physiological structure examination method according to any one of claims 1 to 5 when executing the computer program. The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the fetal cardiovascular physiological structure examination method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, ​

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