Pulmonary nodule traditional Chinese medicine constitution typing method and system fused with iconography signs

Abstract

The invention discloses a pulmonary nodule traditional Chinese medicine constitution typing method and system fused with iconography signs, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting the patient information of a pulmonary nodule patient and image pulmonary nodule feature information; associating the patient information with the traditional Chinese medicine constitution type, associating the image pulmonary nodule feature information with the traditional Chinese medicine constitution type, and constructing a training data set; constructing a pulmonary nodule patient traditional Chinese medicine constitution identification model, and training the pulmonary nodule patient traditional Chinese medicine constitution identification model based on the training data set to obtain an optimal pulmonary nodule patient traditional Chinese medicine constitution identification model; acquiring to-be-tested patient information and to-be-tested image pulmonary nodule feature information of a to-be-tested pulmonary nodule patient, and inputting the to-be-tested patient information and the to-be-tested image pulmonary nodule feature information into the optimal pulmonary nodule patient traditional Chinese medicine constitution identification model to obtain a traditional Chinese medicine constitution type typing result corresponding to the to-be-tested pulmonary nodule patient. The problem that the traditional Chinese medicine constitution typing of the pulmonary nodules cannot be accurately and intelligently judged in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method and system for TCM constitution classification of lung nodules that integrates imaging signs. Background Art

[0002] Pulmonary sarcoidosis is a common clinical disease in thoracic surgery. Its etiology remains unclear, and it can affect multiple systems and organs. Its clinical manifestations lack specificity, making its diagnosis and treatment difficult in clinical practice. Due to its atypical symptoms, the disease is prone to misdiagnosis and missed diagnosis, posing a significant challenge to accurate diagnosis and subsequent effective treatment, severely impacting patient outcomes and prognosis.

[0003] The Traditional Chinese Medicine (TCM) constitution theory holds that individual constitution is closely related to the onset and progression of disease, and that individual constitution determines one's sensitivity to pathogenic factors and the propensity for disease progression. If this theory can be applied to the field of pulmonary sarcoidosis, it is expected to open up new avenues for the prevention and treatment of pulmonary nodules, enabling personalized precision medical intervention. However, the reality is that patients with pulmonary nodules often lack significant clinical manifestations, making the identification and treatment of TCM syndromes more difficult. Furthermore, the current medical field lacks effective technical means for intelligently categorizing the TCM constitution of patients with pulmonary nodules.

[0004] In clinical practice, traditional Chinese medicine (TCM) constitution typing relies heavily on the physician's personal experience, is highly subjective, and has low efficiency, making it difficult to adapt to the current demands of precision medicine. Furthermore, the imaging features of lung nodules contain a wealth of potential disease information, but this information has not been effectively incorporated into the TCM constitution typing process, failing to provide a more comprehensive and accurate basis for constitution determination.

[0005] Therefore, there is an urgent need for a method that can accurately and intelligently determine the Traditional Chinese Medicine constitution type of patients with lung nodules. Summary of the Invention

[0006] In view of this, the present invention proposes a method and system for TCM constitution classification of lung nodules that integrates imaging signs, which can achieve accurate and intelligent determination of TCM constitution classification of lung nodules.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A TCM constitution classification method for pulmonary nodules that integrates imaging signs, including:

[0009] Collect patient information and imaging lung nodule feature information of patients with lung nodules;

[0010] Associate patient information with TCM constitution types, associate imaging lung nodule feature information with TCM constitution types, and construct a training dataset;

[0011] Constructing a TCM constitution identification model for patients with pulmonary nodules, and training the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules;

[0012] Obtain the patient information of the patient with lung nodules to be tested and the characteristic information of the lung nodules in the image to be tested, input the patient information and the characteristic information of the lung nodules in the image to be tested into the optimal TCM constitution identification model for patients with lung nodules, and obtain the TCM constitution type classification result corresponding to the patient with lung nodules to be tested.

[0013] On the basis of the above technical solution, the present invention can also be improved as follows:

[0014] Optionally, associating the patient information with the TCM constitution type includes:

[0015] Associating male patients with lung nodules with a peaceful constitution;

[0016] Associate female patients with lung nodules with a yang deficiency constitution;

[0017] The young and middle-aged group of patients with lung nodules were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution;

[0018] The elderly group of patients with lung nodules were associated with peaceful constitution, yang deficiency constitution and qi deficiency constitution;

[0019] Patients with lung nodules and a family history of tumors were associated with peaceful constitution, yang deficiency constitution, and qi stagnation constitution.

[0020] Optionally, associating the image lung nodule feature information with the TCM constitution type includes:

[0021] Solid lung nodules are associated with peaceful constitution, yang deficiency constitution, and qi deficiency constitution;

[0022] Some solid nodules are associated with the peaceful constitution, the yang deficiency constitution, and the yin deficiency constitution;

[0023] Pure ground glass nodules are associated with yang deficiency constitution, peaceful constitution, and qi stagnation constitution;

[0024] Ground glass nodules and mixed ground glass nodules are associated with a yang deficiency constitution;

[0025] The group with nodule diameter ≤5mm and the group with nodule diameter >5mm and ≤10mm were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution;

[0026] Nodule diameter >10 mm and ≤30 mm was associated with peaceful constitution, yang deficiency constitution, qi deficiency constitution, and yin deficiency constitution.

[0027] Optionally, obtaining the TCM constitution type classification result corresponding to the patient with pulmonary nodules to be tested includes:

[0028] Taking the characteristic information of pulmonary nodules integrated with imaging signs as the dependent variable and the TCM constitution type as the independent variable, the influence of various TCM constitution types on pulmonary nodules was calculated through logistic regression analysis to obtain the TCM constitution type classification results corresponding to the patients with pulmonary nodules to be tested.

[0029] Optionally, the calculation of the degree of influence of various TCM constitution types on pulmonary nodules includes:

[0030] The influence of TCM constitution type on lung nodules was calculated by formula (1);

[0031]

[0032] Where, σ(z) is the influence of TCM constitution type on pulmonary nodules, z is the input of Sigmoid function, e is a natural constant, and -z is the opposite of z;

[0033] When σ(z) is less than 0.5, the TCM constitution type is classified as category 0, and when σ(z) is greater than 0.5, the TCM constitution type is classified as category 1.

[0034] Optionally, the calculation of the influence of TCM constitution type on pulmonary nodules by formula (1) includes:

[0035] Calculate the input of the Sigmoid function through formula (2);

[0036] z=w T x formula (2);

[0037] Where z is the input of the Sigmoid function, x is the classifier input value, and w is the optimal parameter.

[0038] Optionally, the TCM constitution type classification results include balanced constitution, qi deficiency constitution, yang deficiency constitution, yin deficiency constitution, blood stasis constitution, phlegm-damp constitution, damp-heat constitution, qi stagnation constitution and special constitution.

[0039] A TCM constitution classification system for pulmonary nodules that integrates imaging signs, including:

[0040] An acquisition module is used to collect patient information of patients with pulmonary nodules and image pulmonary nodule feature information;

[0041] The training set construction module is used to associate patient information with TCM constitution types, associate imaging lung nodule feature information with TCM constitution types, and construct a training data set;

[0042] A training module is used to construct a TCM constitution identification model for patients with pulmonary nodules, and train the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules;

[0043] The classification module is used to obtain the patient information of the patient with lung nodules to be tested and the characteristic information of the lung nodules in the image to be tested, and input the patient information and the characteristic information of the lung nodules in the image to be tested into the optimal TCM constitution identification model for patients with lung nodules to obtain the TCM constitution type classification result corresponding to the patient with lung nodules to be tested.

[0044] An electronic device comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the steps of the method are implemented when the processor executes the computer program.

[0045] A non-transitory computer-readable storage medium stores a computer program, which implements the steps of the method when executed by a processor.

[0046] The present invention has the following advantages:

[0047] The method of TCM constitution typing for lung nodules that integrates imaging signs in the present invention breaks through the limitation of traditional TCM constitution typing that relies on subjective experience, deeply integrates clinical information such as patient age and medical history with imaging features of lung nodules (such as morphology, density, boundaries, etc.), and accurately mines data associations based on big data training models, upgrading TCM constitution typing from empirical judgment to data-driven, significantly improving classification accuracy and objectivity, and effectively reducing the risk of missed diagnosis and misdiagnosis. Integrating the modern medical imaging sign system into the TCM constitution typing system breaks the disciplinary barriers between TCM theory and imaging technology, creating a new paradigm for TCM diagnosis and treatment of lung nodules, providing a new perspective and technical path for disease mechanism research and syndrome differentiation and treatment, and filling the technical gap in related fields. Based on the optimal TCM constitution identification model for lung nodules, the multi-dimensional data of patients are quickly analyzed, and accurate constitution typing results are automatically generated, transforming the tedious process of manual diagnosis and treatment into automated intelligent processing, greatly improving diagnosis and treatment efficiency, reducing labor costs, and being highly adapted to the needs of large-scale clinical screening and full-course disease management. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] For purposes of illustration and not limitation, the present invention will now be described with reference to embodiments thereof and the accompanying drawings, in which:

[0049] Figure 1 Schematic diagram of the process of TCM constitution typing method for pulmonary nodules integrating imaging signs in an embodiment of the present invention;

[0050] Figure 2 Schematic diagram of the main components of the TCM constitution classification system for pulmonary nodules that integrates imaging signs in an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0053] It should be noted that the terms "first," "second," and the like in the description of the present invention and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate for the embodiments of the present invention described herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatuses.

[0054] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features thereof can be combined with each other. The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0055] Figure 1 FIG. 1 is a flow chart of a method for TCM constitution classification of lung nodules integrating imaging signs in an embodiment of the present invention, as shown in FIG. Figure 1 As shown, the method for TCM constitution classification of lung nodules by integrating imaging signs provided by an embodiment of the present invention includes the following steps S101 to S104.

[0056] S101, collecting patient information of patients with lung nodules and image lung nodule feature information.

[0057] The imaging lung nodule feature information and patient information of patients with lung nodules were collected from CT images. The imaging lung nodule feature information included the number, size, burrs, location, density, malignant signs and other characteristic information of nodules. The patient information included gender, age, height, weight, smoking history, environmental exposure history, previous lung disease history, personal tumor history, family tumor history, etc. At the same time, the "Traditional Chinese Medicine Body Mass Scale" published by the China Association of Traditional Chinese Medicine in 2009 was collected to identify the TCM constitution of patients with lung nodules.

[0058] S102, associating patient information with TCM constitution types, associating image lung nodule feature information with TCM constitution types, and constructing a training data set.

[0059] Associating male patients with lung nodules with a peaceful constitution;

[0060] Associate female patients with lung nodules with a yang deficiency constitution;

[0061] The young and middle-aged group of patients with lung nodules were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution;

[0062] The elderly group of patients with lung nodules were associated with peaceful constitution, yang deficiency constitution and qi deficiency constitution;

[0063] Patients with lung nodules and a family history of tumors were associated with peaceful constitution, yang deficiency constitution, and qi stagnation constitution.

[0064] Solid lung nodules are associated with peaceful constitution, yang deficiency constitution, and qi deficiency constitution;

[0065] Some solid nodules are associated with the peaceful constitution, the yang deficiency constitution, and the yin deficiency constitution;

[0066] Pure ground glass nodules are associated with yang deficiency constitution, peaceful constitution, and qi stagnation constitution;

[0067] Ground glass nodules and mixed ground glass nodules are associated with a yang deficiency constitution;

[0068] The group with nodule diameter ≤5mm and the group with nodule diameter >5mm and ≤10mm were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution;

[0069] Nodule diameter >10 mm and ≤30 mm was associated with peaceful constitution, yang deficiency constitution, qi deficiency constitution, and yin deficiency constitution.

[0070] S103, constructing a TCM constitution identification model for patients with pulmonary nodules, and training the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules.

[0071] S104, obtaining the patient information of the patient with the pulmonary nodules to be tested and the characteristic information of the pulmonary nodules in the image to be tested, inputting the patient information and the characteristic information of the pulmonary nodules in the image to be tested into the optimal TCM constitution identification model for the patient with the pulmonary nodules to be tested, and obtaining the TCM constitution type classification result corresponding to the patient with the pulmonary nodules to be tested.

[0072] Using the characteristic information of pulmonary nodules integrated with imaging signs as the dependent variable and the TCM constitution type as the independent variable, logistic regression analysis was performed to calculate the degree of influence of various TCM constitution types on pulmonary nodules. This yielded the TCM constitution classification results corresponding to the patients with pulmonary nodules, namely the odds ratio (OR) and its 95% confidence interval (95% CI). Among them, TCM constitution types are divided into nine types: balanced constitution, qi deficiency constitution, yang deficiency constitution, yin deficiency constitution, phlegm-damp constitution, damp-heat constitution, blood stasis constitution, qi stagnation constitution, and special constitution. The balanced constitution was used as the reference group.

[0073] When constructing the logistic regression model, stepwise regression was used to screen independent variables to control for other potentially influencing factors. Covariates in the model included sex, age, height, weight, smoking history, environmental exposure history, previous history of lung disease, personal cancer history, and family cancer history. The influence of different TCM constitution types on pulmonary nodules was assessed by calculating partial regression coefficients and odds ratios (ORs) for each independent variable.

[0074] Logistic regression is a classic classification method in statistical learning. It belongs to the log-linear model and is therefore also known as log-probability regression. It is a commonly used statistical analysis method that can assess the impact of various factors on the probability of an event. The main idea behind logistic regression classification is to establish a regression equation for the classification boundary based on the existing data and then use this equation to perform classification. The term "regression" here comes from the concept of "best fit parameters," meaning the goal is to find the optimal set of parameters.

[0075] What we want is a function that accepts all inputs and predicts the class. For example, in the case of two classes, the above function outputs either 0 or 1. There is a function that has similar properties (it can output either 0 or 1) and is mathematically easier to handle: the sigmoid function.

[0076] The influence of TCM constitution type on lung nodules was calculated by formula (1);

[0077]

[0078] Where, σ(z) is the influence of TCM constitution type on pulmonary nodules, z is the input of Sigmoid function, e is a natural constant, and -z is the opposite of z;

[0079] When σ(z) is less than 0.5, the TCM constitution type is classified as category 0, and when σ(z) is greater than 0.5, the TCM constitution type is classified as category 1.

[0080] Calculate the input of the Sigmoid function through formula (2);

[0081] z=w T x formula (2);

[0082] Where z is the input of the Sigmoid function, x is the classifier input value, and w is the optimal parameter.

[0083] The patient information and the characteristic information of the lung nodules in the images to be tested are input into the optimal TCM constitution identification model for lung nodules to obtain the TCM constitution type classification results and TCM solutions corresponding to the lung nodules. For example, if the patient's TCM constitution is mainly qi deficiency, damp-heat, yin deficiency, and qi stagnation, then the treatment method is mainly to invigorate qi and strengthen the spleen, clear away heat and dampness, nourish yin and moisten dryness, soothe the liver and regulate qi, and promote blood circulation, resolve phlegm and disperse nodules. By improving the TCM constitution, the nodule lesions can be stabilized and malignant transformation can be prevented, providing a reference for the clinical treatment of lung nodules.

[0084] Figure 2 Schematic diagram of the main components of the TCM constitution classification system for lung nodules that integrates imaging signs in an embodiment of the present invention. Figure 2 As shown, the TCM constitution classification system 1 for pulmonary nodules that integrates imaging signs provided by an embodiment of the present invention includes an acquisition module 10 , a training set construction module 20 , a training module 30 and a classification module 40 .

[0085] An acquisition module 10 is used to acquire patient information of patients with pulmonary nodules and image pulmonary nodule feature information;

[0086] A training set construction module 20 is used to associate patient information with TCM constitution types, associate image lung nodule feature information with TCM constitution types, and construct a training data set;

[0087] A training module 30 is used to construct a TCM constitution identification model for patients with pulmonary nodules, and train the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules;

[0088] The classification module 40 is used to obtain the patient information of the patient with lung nodules to be tested and the characteristic information of the lung nodules in the image to be tested, and input the patient information and the characteristic information of the lung nodules in the image to be tested into the optimal TCM constitution identification model for patients with lung nodules to obtain the TCM constitution type classification result corresponding to the patient with lung nodules to be tested.

[0089] Figure 3A schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention, such as Figure 3 As shown, the electronic device 50 includes: a processor 501 (processor), a memory 502 (memory) and a bus 503;

[0090] The processor 501 and the memory 502 communicate with each other via the bus 503.

[0091] The processor 501 is used to call the program instructions in the memory 502 to execute the methods provided by the above-mentioned method embodiments, so as to execute the methods provided by the implementation methods of the present invention.

[0092] This embodiment provides a non-transitory computer-readable storage medium, which stores computer instructions. The computer instructions enable a computer to execute the method provided by the embodiment of the present invention.

[0093] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk, etc. Various storage media that can store program codes.

[0094] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for TCM constitution typing of pulmonary nodules integrating imaging signs, characterized in that: include: Collect patient information and imaging lung nodule feature information of patients with lung nodules; Associate patient information with TCM constitution types, associate imaging lung nodule feature information with TCM constitution types, and construct a training dataset; Constructing a TCM constitution identification model for patients with pulmonary nodules, and training the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules; Obtain the patient information of the patient with lung nodules to be tested and the characteristic information of the lung nodules in the image to be tested, input the patient information and the characteristic information of the lung nodules in the image to be tested into the optimal TCM constitution identification model for patients with lung nodules, and obtain the TCM constitution type classification result corresponding to the patient with lung nodules to be tested.

2. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 1, characterized in that: The associating the patient information with the TCM constitution type includes: Associating male patients with lung nodules with a peaceful constitution; Associate female patients with lung nodules with a yang deficiency constitution; The young and middle-aged group of patients with lung nodules were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution; The elderly group of patients with lung nodules were associated with peaceful constitution, yang deficiency constitution and qi deficiency constitution; Patients with lung nodules and a family history of tumors were associated with peaceful constitution, yang deficiency constitution, and qi stagnation constitution.

3. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 1, characterized in that: The step of associating the image lung nodule feature information with the TCM constitution type includes: Solid lung nodules are associated with peaceful constitution, yang deficiency constitution, and qi deficiency constitution; Some solid nodules are associated with the peaceful constitution, the yang deficiency constitution, and the yin deficiency constitution; Pure ground glass nodules are associated with yang deficiency constitution, peaceful constitution, and qi stagnation constitution; Ground glass nodules and mixed ground glass nodules are associated with a yang deficiency constitution; The group with nodule diameter ≤5mm and the group with nodule diameter >5mm and ≤10mm were associated with Yang deficiency constitution, peaceful constitution and Qi stagnation constitution; Nodule diameter >10 mm and ≤30 mm was associated with peaceful constitution, yang deficiency constitution, qi deficiency constitution, and yin deficiency constitution.

4. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 1, characterized in that: The TCM constitution type classification result corresponding to the patient with pulmonary nodules to be tested is obtained, including: Taking the characteristic information of pulmonary nodules integrated with imaging signs as the dependent variable and the TCM constitution type as the independent variable, the influence of various TCM constitution types on pulmonary nodules was calculated through logistic regression analysis to obtain the TCM constitution type classification results corresponding to the patients with pulmonary nodules to be tested.

5. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 4, characterized in that: The calculation of the influence of various TCM constitution types on lung nodules includes: The influence of TCM constitution type on lung nodules was calculated by formula (1); Where, σ(z) is the influence of TCM constitution type on pulmonary nodules, z is the input of Sigmoid function, e is a natural constant, and -z is the opposite of z; When σ(z) is less than 0.5, the TCM constitution type is classified as category 0, and when σ(z) is greater than 0.5, the TCM constitution type is classified as category 1.

6. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 5, characterized in that: The influence degree of TCM constitution type on lung nodules is calculated by formula (1), including: Calculate the input of the Sigmoid function through formula (2); z=w T x formula (2); Where z is the input of the Sigmoid function, x is the classifier input value, and w is the optimal parameter.

7. The method for TCM constitution typing of pulmonary nodules based on integration of imaging signs according to claim 1, characterized in that: The TCM constitution classification results include balanced constitution, qi deficiency constitution, yang deficiency constitution, yin deficiency constitution, blood stasis constitution, phlegm-damp constitution, damp-heat constitution, qi stagnation constitution and special constitution.

8. A system for TCM constitution classification of pulmonary nodules that integrates imaging signs, characterized by: include: An acquisition module is used to collect patient information of patients with pulmonary nodules and image pulmonary nodule feature information; The training set construction module is used to associate patient information with TCM constitution types, associate imaging lung nodule feature information with TCM constitution types, and construct a training data set; A training module is used to construct a TCM constitution identification model for patients with pulmonary nodules, and train the TCM constitution identification model for patients with pulmonary nodules based on the training data set to obtain an optimal TCM constitution identification model for patients with pulmonary nodules; The classification module is used to obtain the patient information of the patient with lung nodules to be tested and the characteristic information of the lung nodules in the image to be tested, and input the patient information and the characteristic information of the lung nodules in the image to be tested into the optimal TCM constitution identification model for patients with lung nodules to obtain the TCM constitution type classification result corresponding to the patient with lung nodules to be tested.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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