Thyroid nodule evaluation system based on ultrasonic image

Abstract

The invention relates to the technical field of ultrasonic image analysis, and discloses a thyroid nodule evaluation system based on ultrasonic image.The system obtains medical record data and medical examination data of patients through a multi-dimensional collection module, the medical record data and the medical examination data are classified to form a data set, and an intelligent evaluation module analyzes the thyroid function state of each patient and generates function coefficients; the image quality of each group of ultrasonic images is analyzed, a corresponding detection data group Jcsj is generated, a unified evaluation standard is established, key frames are rapidly screened out from a large amount of ultrasonic image data, the multi-dimensional integration efficiency is high, the intelligent evaluation module sets a threshold value of a fixed range, and the nodule volume and the nodule score are analyzed and generated in combination with a medical data set. The function coefficient, the detection data set and the nodule score are combined, the risk level of the thyroid nodule of the patient and the image quality of the ultrasonic image are evaluated, the ultrasonic image key frame is screened, the treatment suggestion is output, and the intelligent evaluation precision is high.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasonic image analysis, and particularly to a thyroid nodule evaluation system based on ultrasonic images. Background Art

[0002] A thyroid nodule refers to a localized mass formed by abnormal proliferation of thyroid cells and is a common thyroid disease. Abnormal iodine intake is one of the common factors. When iodine is deficient, the synthesis of thyroid hormones is insufficient, and the thyroid gland will proliferate compensatorily to form nodules. Excessive iodine may also interfere with the normal function of the thyroid gland and induce nodules. In addition, long-term mental stress and a living environment with chemical radiation are all possible incentives for the growth of thyroid nodules. The symptoms of thyroid nodules vary. Most patients have no obvious symptoms and are often discovered during physical examinations. Some patients may have a neck mass that can move up and down with swallowing movements and may sometimes be accompanied by symptoms such as pain and hoarseness. If the nodule is large, it may compress the surrounding tissues, causing problems such as difficulty breathing and swallowing. Thyroid nodules can be divided into benign and malignant. Benign nodules grow slowly, have clear boundaries, and are relatively soft in texture, while malignant nodules grow rapidly, have irregular boundaries, and are hard in texture. Once a thyroid nodule is discovered, it is necessary to seek medical attention in a timely manner, and the nature of the nodule is clarified through means such as ultrasonic examination, CT examination, and fine needle aspiration biopsy. For benign nodules, regular reexaminations or medical treatments can be carried out according to the situation. If it is a malignant nodule, surgical treatment is required, and comprehensive treatment measures such as radiotherapy and chemotherapy are combined to ensure the health of the patient.

[0003] Currently, traditional thyroid nodule evaluation systems based on ultrasonic images have insufficient ability to distinguish between cystic nodules and solid nodules, are prone to overdiagnosis, missed diagnosis, and misjudgment of complex nodules, have low treatment efficiency, lack an effective data integration mechanism and a unified evaluation standard, and limit the accuracy of comprehensive diagnosis. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a thyroid nodule evaluation system based on ultrasonic images, which has the advantages of high multi-dimensional integration efficiency and high intelligent evaluation accuracy, and solves the problems of insufficient discrimination ability and low comprehensive diagnosis accuracy of traditional thyroid nodule evaluation systems based on ultrasonic images.

[0006] (2) Technical Solutions

[0007] To achieve the above object, the present invention provides the following technical solution: A thyroid nodule evaluation system based on ultrasonic images, including a multi-dimensional acquisition module and an intelligent evaluation module;

[0008] The multi-dimensional acquisition module consists of a patient data unit and an examination data unit. The patient data unit collects a patient data set through a network connection to an electronic medical record system. The patient data set includes the medical record data of all patients. The examination data unit collects a medical data set through a network connection to a color Doppler ultrasound diagnostic instrument and a CT scanner. The medical data set includes the medical examination data of all patients;

[0009] The intelligent evaluation module consists of a function analysis unit, an image analysis unit, and an evaluation management unit. The function analysis unit analyzes the thyroid function status of each patient based on the patient data set and generates a corresponding function coefficient Gnx. The image analysis unit analyzes the picture quality of each group of ultrasound images based on the medical data set and generates a corresponding detection data group Jcsj. The image analysis unit is set with a fixed range of length threshold CDY, volume threshold TJY, and intensity threshold QDY. Combining with the medical data set, it analyzes and generates a nodule volume TJ and a nodule score Jep. The evaluation management unit is set with a fixed range of function threshold GNY, score threshold JEPY, rate ratio threshold LBY, range threshold JCY, and comparison threshold DBY. Combining with the function coefficient Gnx, the detection data group Jcsj, and the nodule score Jep, it evaluates the risk level of the patient's thyroid nodules and the picture quality of the ultrasound images, screens the key frames of the ultrasound images, and outputs treatment suggestions.

[0010] Preferably, the expression of the patient data set is {H1 l 、H2 l 、H3 l 、...、Hz l}, where H1 l to Hz l represent the medical record data of the first to the z-th patients. The medical record data includes the patient's name, height, weight, high-risk environment exposure frequency, TSH index, FT3 index, and FT4 index, and l represents the patient's age.

[0011] Preferably, the expression of the medical data set is {Y1 s 、Y2 s 、Y3 s 、...、Yx s}, where Y1 s to Yx s represent the first to the x-th groups of medical examination data. The medical examination data includes the patient's name, ultrasonic frequency, spatial resolution, pixel value, frame rate, gray-scale contrast, number of nodules, transverse diameter of nodules, longitudinal diameter of nodules, nodule morphology, nodule edge, nodule echo intensity, and nodule blood supply level, and s represents the specific time point for collecting the medical examination data.

[0012] Preferably, the calculation process of the function coefficient Gnx is as follows:

[0013] Extract the medical record data of the i-th patient from the patient data set, and mark the height of the i-th patient as sg i , mark the weight of the i-th patient as tz i , mark the high-risk environmental exposure frequency of the i-th patient as bl i , mark the TSH index of the i-th patient as TSH i , mark the FT3 index of the i-th patient as FT3 i , mark the FT4 index of the i-th patient as FT3 i , mark the age of the i-th patient as i l ;

[0014]

[0015] In the formula, BMI i represents the body mass index of the i-th patient;

[0016]

[0017] In the formula, α1 represents the weight for the patient's body mass index, α2 represents the weight for the ratio of the patient's age to the high-risk environmental exposure frequency, α3 represents the weight for the patient's TSH index, α4 represents the weight for the patient's FT3 index, α5 represents the weight for the patient's FT4 index. α1, α2, α3, α4, and α5 are all constants, and α1 + α2 + α3 + α4 + α5 = 1, represents the functional coefficient Gnx of the i-th patient calculated according to the weights of α1, α2, α3, α4, and α5 i .

[0018] Preferably, the calculation process of the detection data group Jcsj is as follows:

[0019] Extract the medical examination data of the i-th patient from the medical data set, and mark the ultrasonic frequency during the i-th patient's single ultrasound examination as bp, mark the spatial resolution of the i-th patient's single group of ultrasound images as kf, mark the pixel value of the i-th patient's single group of ultrasound images as xs, mark the frame rate during the i-th patient's single ultrasound examination as zl, and mark the gray-scale contrast of the i-th patient's single group of ultrasound images as hd;

[0020]

[0021] In the formula, represents the ratio of the ultrasonic frequency to the spatial resolution of the ultrasound image, xs max and xs min are respectively the maximum and minimum values of the pixel values of the i-th patient's single group of ultrasound images, xsmax -xs min represents the range of pixel values of the single-group ultrasound image of the i-th patient. represents the ratio of the frame rate to the gray-scale contrast of the ultrasound image, Jcsj i represents the detection data group Jcsj corresponding to the single ultrasound examination of the i-th patient i .

[0022] Preferably, the calculation process of the nodule volume TJ is as follows:

[0023] Extract the medical examination data of the i-th patient from the medical data set, and mark the transverse diameter of the nodule detected by CT of the i-th patient as hj i , and mark the longitudinal diameter of the nodule detected by CT of the i-th patient as zj i ;

[0024] TJ i = hj i × zj i

[0025] In the formula, TJ i represents the nodule volume of the i-th patient.

[0026] 8. Preferably, the analysis process of the nodule score Jep is as follows:

[0027] When the number of nodules of the i-th patient is greater than 1, the nodule score Jep of the i-th patient i is incremented by 1;

[0028] When the transverse diameter hj of the nodule of the i-th patient i exceeds the length threshold CDY or the longitudinal diameter zj of the nodule of the i-th patient i exceeds the longitudinal diameter threshold ZJY, the nodule score Jep of the i-th patient i is incremented by 1;

[0029] When the nodule volume TJ of the i-th patient i exceeds the volume threshold TJY, the nodule score Jep of the i-th patient i is incremented by 1;

[0030] When the nodule shape of the i-th patient is irregular, the nodule score Jep of the i-th patient i is incremented by 1;

[0031] When the nodule edge of the i-th patient is blurred, the nodule score Jep of the i-th patient i is incremented by 1;

[0032] When the nodule echo intensity of the i-th patient is lower than the intensity threshold QDY, the nodule score Jep of the i-th patient i is incremented by 1;

[0033] When the nodule echo intensity of the i-th patient exceeds the intensity threshold QDY, the nodule score Jep of the i-th patient i is increased by 2;

[0034] When the nodule of the i-th patient has an irregular shape and a blurred nodule edge, the nodule score Jep of the i-th patient i is increased by 3;

[0035] When the blood supply grade of the nodule of the i-th patient is higher than grade I, the nodule score Jep of the i-th patient i is increased by 2.

[0036] Preferably, when the function coefficient Gnx exceeds the function threshold GNY, it indicates that the thyroid function status of the patient is abnormal, and the corresponding risk level is low. It is recommended that the patient have an ultrasound examination in time.

[0037] Preferably, when the number of nodules is greater than 1 and the nodule score Jep is included in the score threshold JEPY, it indicates that the risk level corresponding to the thyroid nodules of the patient is medium. The evaluation management unit screens the key frames of the ultrasound images according to the detection data group Jcsj, and its screening process is as follows:

[0038] If in the detection data group Jcsj, the ratio of the ultrasonic frequency to the spatial resolution of the ultrasound image is included in the rate ratio threshold LBY, the range of the pixel values of the ultrasound image is included in the range threshold JCY, and the ratio of the frame rate to the gray-scale contrast of the ultrasound image is included in the contrast threshold DBY, it indicates that the picture quality of the ultrasound image is good, that is, the key frame.

[0039] Preferably, when the nodule score Jep exceeds the score threshold JEPY, it indicates that the risk level corresponding to the thyroid nodules of the patient is high. It is recommended to perform a fine needle aspiration biopsy in time.

[0040] Compared with the prior art, the present invention provides a thyroid nodule evaluation system based on ultrasound images, which has the following beneficial effects:

[0041] 1. In the present invention, the multi-dimensional acquisition module is connected to the electronic medical record system, the color Doppler ultrasound diagnostic instrument and the CT scanner to obtain the medical record data and medical examination data of all patients, and classify and form a patient data set and a medical data set. The intelligent evaluation module analyzes the thyroid function status of each patient according to the patient data set and generates the corresponding function coefficient Gnx, comprehensively analyzes the different physiological indexes of the patient, and comprehensively understands the health status of the patient. The intelligent evaluation module analyzes the picture quality of each group of ultrasound images according to the examination data set and generates the corresponding detection data group Jcsj, establishes a unified evaluation standard, and quickly screens out the key frames from a large amount of ultrasound image data, with high multi-dimensional integration efficiency.

[0042] 2. The present invention sets length threshold CDY, volume threshold TJY, and intensity threshold QDY within a fixed range through an intelligent evaluation module. Then, in combination with a medical data set, it analyzes and generates nodule volume TJ and nodule score Jep. The higher the final score, the more urgently the patient needs treatment. The intelligent evaluation module sets functional threshold GNY, score threshold JEPY, rate ratio threshold LBY, range difference threshold JCY, and comparison threshold DBY within a fixed range. Then, in combination with functional coefficient Gnx, detection data set Jcsj, and nodule score Jep, it evaluates the risk level of the patient's thyroid nodule and the picture quality of the ultrasound image, screens key frames of the ultrasound image, and outputs treatment suggestions, with high intelligent evaluation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic structural diagram of the system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] Since the traditional ultrasound image-based thyroid nodule evaluation system has insufficient ability to distinguish between cystic nodules and solid nodules, it is prone to overdiagnosis, missed diagnosis, and misjudgment of complex nodules, with low treatment efficiency, lack of effective data integration mechanism and unified evaluation criteria, which limits the accuracy of comprehensive diagnosis. Therefore, a thyroid nodule evaluation system based on ultrasound images is provided. Please refer to Figure 1 A thyroid nodule evaluation system based on ultrasound images includes a multi-dimensional acquisition module and an intelligent evaluation module;

[0046] The multi-dimensional acquisition module consists of a patient data unit and an examination data unit. The patient data unit collects a patient data set through a network connection to an electronic medical record system. The patient data set includes the medical record data of all patients. The expression of the patient data set is {H1 l , H2 l , H3 l ,..., Hz l}, where H1 l to Hz lRepresents the medical record data of the first to zth patients. The medical record data includes patient name, height, weight, frequency of exposure to high-risk environments, TSH index, FT3 index, and FT4 index. l represents the patient's age. Long-term exposure to harmful environments such as radiation and chemicals also increases the risk of developing thyroid nodules. Thyroid-stimulating hormone TSH can stimulate the thyroid gland to synthesize and release free triiodothyronine FT3 and free thyroxine FT4. By monitoring the changes in the levels of TSH, FT3, and FT4, the functional status of the thyroid gland can be evaluated more accurately;

[0047] The inspection data unit collects a medical data set by connecting a color Doppler ultrasound diagnostic instrument and a CT scanner through a network. The medical data set includes the medical examination data of all patients. The expression of the medical data set is {Y1 s 、Y2 s 、Y3 s 、...、Yx s}, where Y1 s to Yx s represent the medical examination data of the first to xth groups. The medical examination data includes patient name, ultrasonic frequency, spatial resolution, pixel value, frame rate, gray-scale contrast, number of nodules, transverse diameter of nodules, longitudinal diameter of nodules, nodule morphology, nodule edge, nodule echo intensity, and nodule blood supply grade. Specifically, the ultrasonic frequency, spatial resolution, pixel value, frame rate, gray-scale contrast, nodule morphology, nodule edge, nodule echo intensity, and nodule blood supply grade parameters are provided by the color Doppler ultrasound diagnostic instrument, and the number of nodules, transverse diameter of nodules, and longitudinal diameter of nodules parameters are provided by the CT scanner. In the actual evaluation process, the nodule echo intensity includes low intensity, medium intensity, and high intensity. Low intensity indicates that the nodule contains more liquid or cystic components, medium intensity indicates that the internal tissue of the nodule is uniform, and high intensity indicates that the nodule contains more substantial components. The nodule blood supply grade is divided into grades I-III. Grade I indicates that there is very little or no blood supply inside the nodule, which is usually a characteristic of a benign nodule. Grade II indicates that there is less blood supply inside the nodule, and both benign and malignant nodules have a certain probability. Grade III indicates that there is very rich blood supply inside the nodule, with a large number of blood vessels supplying, which is usually a characteristic of a malignant nodule. s represents the specific time point for collecting the medical examination data. Multidimensional data helps in the subsequent analysis and evaluation of the nature of thyroid nodules and formulating corresponding treatment plans;

[0048] The intelligent evaluation module consists of a function analysis unit, an image analysis unit, and an evaluation management unit. The function analysis unit analyzes the functional status of each patient based on the patient data set and generates a corresponding function coefficient Gnx. The calculation process is as follows:

[0049] According to the patient data set, extract the medical record data of the ith patient and mark the height of the ith patient as sg i and mark the weight of the ith patient as tzi Mark the high-risk environmental exposure frequency of the i-th patient as bl i Mark the TSH index of the i-th patient as TSH i Mark the FT3 index of the i-th patient as FT3 i Mark the FT4 index of the i-th patient as FT3 i Mark the age of the i-th patient as i l ;

[0050]

[0051] In the formula, BMI i represents the body mass index of the i-th patient;

[0052]

[0053] In the formula, α1 represents the weight for the patient's body mass index, α2 represents the weight for the ratio of the patient's age to the high-risk environmental exposure frequency, α3 represents the weight for the patient's TSH index, α4 represents the weight for the patient's FT3 index, α5 represents the weight for the patient's FT4 index. α1, α2, α3, α4, and α5 are all constants, and α1 + α2 + α3 + α4 + α5 = 1. represents the functional coefficient Gnx of the i-th patient calculated according to the weights of α1, α2, α3, α4, and α5 i Comprehensively analyzing the different physiological indicators of the patient helps to comprehensively understand the patient's health status;

[0054] The image analysis unit analyzes the picture quality of each group of ultrasonic images based on the ultrasonic data set and generates the corresponding detection data set Jcsj. Its calculation process is as follows:

[0055] Extract the medical examination data of the i-th patient according to the examination data set, mark the ultrasonic frequency during the i-th patient's single ultrasonic examination as bp, mark the spatial resolution of the i-th patient's single group of ultrasonic images as kf, mark the pixel value of the i-th patient's single group of ultrasonic images as xs, mark the frame rate during the i-th patient's single ultrasonic examination as zl, and mark the gray-scale contrast of the i-th patient's single group of ultrasonic images as hd;

[0056]

[0057] In the formula, represents the ratio of the ultrasonic frequency to the spatial resolution of the ultrasonic image, xs max and xs min are respectively the maximum and minimum values of the pixel value of the i-th patient's single group of ultrasonic images, xs max -xsmin represents the range of pixel values of the single-group ultrasound image of the i-th patient, represents the ratio of the frame rate to the gray-scale contrast of the ultrasound image, Jcsj i represents the detection data set Jcsj corresponding to the single ultrasound examination of the i-th patient i , establish a unified evaluation standard, quickly screen out key frames from a large number of ultrasound image data, and have high multi-dimensional integration efficiency;

[0058] The image analysis unit is set with a fixed-range length threshold CDY, volume threshold TJY, and intensity threshold QDY, and then combined with the ultrasound data set to analyze and generate the nodule volume TJ and nodule score Jep;

[0059] The calculation process of the nodule volume TJ is as follows:

[0060] According to the examination data set, extract the medical examination data of the i-th patient, and mark the transverse diameter of the nodule detected by CT of the i-th patient as hj i , mark the longitudinal diameter of the nodule detected by CT of the i-th patient as zj i ;

[0061] TJ i = hj i × zj i

[0062] In the formula, TJ i represents the nodule volume of the i-th patient;

[0063] The analysis process of the nodule score Jep is as follows:

[0064] If the number of nodules of the i-th patient is greater than 1, the nodule score Jep of the i-th patient i is incremented by 1;

[0065] If the transverse diameter hj of the nodule of the i-th patient i exceeds the length threshold CDY or the longitudinal diameter zj of the nodule of the i-th patient i exceeds the longitudinal diameter threshold ZJY, the nodule score Jep of the i-th patient i is incremented by 1;

[0066] If the nodule volume TJ of the i-th patient i exceeds the volume threshold TJY, the nodule score Jep of the i-th patient i is incremented by 1;

[0067] If the nodule shape of the i-th patient is irregular, the nodule score Jep of the i-th patient i is incremented by 1;

[0068] If the nodule edge of the i-th patient is blurred, the nodule score Jep of the i-th patient iIncrement by 1;

[0069] If the nodule echo intensity of the i-th patient is lower than the intensity threshold QDY, it indicates that the nodule contains more liquid or cystic components, and the probability of a cystic nodule is relatively high. The nodule score Jep of the i-th patient i Increment by 1;

[0070] If the nodule echo intensity of the i-th patient exceeds the intensity threshold QDY, it indicates that the nodule contains more solid components, and the probability of a solid nodule is relatively high. The nodule score Jep of the i-th patient i Increment by 2;

[0071] If the nodule shape of the i-th patient is irregular and the nodule margin is blurred, the nodule score Jep of the i-th patient i Increment by 3;

[0072] If the blood supply grade of the nodule of the i-th patient is higher than grade I, the nodule score Jep of the i-th patient i Increment by 2. The higher the final score, the more urgent the treatment is required for the patient;

[0073] The evaluation management unit is set with functional thresholds GNY, scoring thresholds JEPY, rate ratio thresholds LBY, range difference thresholds JCY, and comparison thresholds DBY within a fixed range. Combining with the functional coefficient Gnx, the detection data group Jcsj, and the nodule score Jep, it evaluates the risk level of the patient's thyroid nodule and the picture quality of the ultrasound image. When the functional coefficient Gnx exceeds the functional threshold GNY, it indicates that the patient's thyroid function status is abnormal, and the corresponding risk level is low. It is recommended that the patient have an ultrasound examination in a timely manner. When the number of nodules is greater than 1 and the nodule score Jep is included in the scoring threshold JEPY, it indicates that the risk level corresponding to the patient's thyroid nodule is medium. The evaluation management unit screens the key frames of the ultrasound image according to the detection data group Jcsj, and its screening process is as follows:

[0074] If in the detection data group Jcsj, the ratio of the ultrasonic frequency to the spatial resolution of the ultrasound image is included in the rate ratio threshold LBY, the range of pixel values of the ultrasound image is included in the range difference threshold JCY, and the ratio of the frame rate to the gray-scale contrast of the ultrasound image is included in the comparison threshold DBY, it indicates that the picture quality of the ultrasound image is good, that is, it is a key frame;

[0075] When the nodule score Jep exceeds the scoring threshold JEPY, it indicates that the risk level corresponding to the patient's thyroid nodule is high. It is recommended to perform a fine needle aspiration biopsy in a timely manner. Small nodules may not require immediate treatment, while large nodules may require surgical resection, and the intelligent evaluation has high accuracy.

[0076] Example 1:

[0077] In this embodiment, a 35-year-old young male with a height of 1.75 m is selected as the experimental subject. After testing, the weight of this young man is 70 kg, the high-risk environment exposure frequency is 7 times / month, the TSH index is 2 mIU / L, the FT3 index is 3.5 pmol / L, and the FT4 index is 12 pmol / L. The calculation process of the functional coefficient Gnx of this young man is as follows:

[0078]

[0079] In the formula, the body mass index BMI of this young man i is 22.9, 0.2 represents the weight for the patient's body mass index, 0.2 represents the weight for the ratio of the patient's age to the high-risk environment exposure frequency, 0.2 represents the weight for the patient's TSH index, 0.2 represents the weight for the patient's FT3 index, 0.2 represents the weight for the patient's FT4 index, α1, α2, α3, α4, and α5 are all constants, and 0.2 + 0.2 + 0.2 + 0.2 + 0.2 = 1. According to the weights of α1, α2, α3, α4, and α5, the functional coefficient Gnx of this young man i is 9.08.

[0080] Example 2:

[0081] In this embodiment, a color Doppler ultrasound diagnostic instrument with a frequency of 2 MHz and a frame rate of 60 frames per second is selected as the experimental subject. After testing, the spatial resolution of the obtained ultrasonic image is 0.5 mm, the range of pixel values is 50 - 255, and the gray-scale contrast is 12. The calculation process of the detection data group Jcsj of this group of ultrasonic images is as follows:

[0082]

[0083] In the formula, 0.25 represents the ratio of the ultrasonic frequency to the spatial resolution of the ultrasonic image, 205 represents the range of pixel values of a single group of ultrasonic images of the i-th patient, and 0.2 represents the ratio of the frame rate to the gray-scale contrast of the ultrasonic image.

[0084] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The thyroid nodule assessment system based on ultrasound imaging is characterized by: Including multi-dimensional acquisition module and intelligent evaluation module; The multi-dimensional acquisition module is composed of a patient data unit and an examination data unit. The patient data unit is connected to the electronic medical record system through a network to collect patient data sets, and the patient data sets include medical record data of all patients. The examination data unit is connected to a color Doppler ultrasound diagnostic instrument and a CT scanner through a network to collect medical data sets, and the medical data sets include medical examination data of all patients. The intelligent evaluation module consists of a function analysis unit, an image analysis unit and an evaluation management unit. The function analysis unit analyzes the thyroid function status of each patient according to the patient data set and generates a corresponding function coefficient Gnx. The image analysis unit analyzes the picture quality of each group of ultrasound images according to the medical data set and generates a corresponding detection data group Jcsj. The image analysis unit is provided with a fixed range of length threshold CDY, volume threshold TJY and intensity threshold QDY, and then combined with the medical data set, analyzes and generates nodule volume TJ and nodule score Jep. The evaluation management unit is provided with a fixed range of function threshold GNY, score threshold JEPY, rate ratio threshold LBY, extreme difference threshold JCY and contrast threshold DBY, and then combined with the function coefficient Gnx, the detection data group Jcsj and the nodule score JeP, evaluates the risk level of the patient's thyroid nodules and the picture quality of the ultrasound image, screens ultrasound image key frames and outputs treatment recommendations.

2. The thyroid nodule assessment system based on ultrasound imaging according to claim 1, characterized in that: The expression of the patient data set is {H1 l 、H2 l 、H3 l , ..., Hz l }, H1 l to Hz l represents the medical record data of the first to zth patients, including the patient's name, height, weight, frequency of exposure to high-risk environments, TSH index, FT3 index and FT4 index, and l represents the patient's age.

3. The thyroid nodule assessment system based on ultrasound imaging according to claim 2, characterized in that: The expression of the medical data set is {Y1 s 、Y2 s 、Y3 s ,...,Yx s }, Y1 s To Yx s represents the first to xth groups of medical examination data, which include patient name, ultrasound frequency, spatial resolution, pixel value, frame rate, grayscale contrast, number of nodules, nodule transverse diameter, nodule longitudinal diameter, nodule morphology, nodule edge, nodule echo intensity and nodule blood supply grade. s represents the specific time point for collecting the medical examination data.

4. The ultrasound imaging-based thyroid nodule assessment system according to claim 3, characterized in that: The calculation process of the functional coefficient Gnx is as follows: According to the patient data set, extract the medical record data of the i-th patient and mark the height of the i-th patient as sg i , label the weight of the i-th patient as tz i , mark the high-risk environment exposure frequency of the i-th patient as bl i , the TSH index of the i-th patient is marked as TSH i , the FT3 index of the i-th patient is marked as FT3 i , the FT4 index of the i-th patient is marked as FT3 i , label the age of the i-th patient as i l ; In the formula, BMI i represents the body mass index of the i-th patient; In the formula, α1 represents the weight for the patient's body mass index, α2 represents the weight for the ratio of the patient's age to the frequency of exposure to high-risk environments, α3 represents the weight for the patient's TSH index, α4 represents the weight for the patient's FT3 index, and α5 represents the weight for the patient's FT4 index. α1, α2, α3, α4, and α5 are all constants, and α1+α2+α3+α4+α5=1. Indicates that the functional coefficient Gnx of the i-th patient is calculated according to the weights α1, α2, α3, α4 and α5 i .

5. The ultrasound imaging-based thyroid nodule assessment system according to claim 4, characterized in that: The calculation process of the detection data set Jcsj is as follows: According to the medical data set, the medical examination data of the i-th patient is extracted, and the ultrasonic frequency of the i-th patient in a single ultrasound examination is marked as bp, the spatial resolution of the i-th patient's single set of ultrasound images is marked as kf, the pixel value of the i-th patient's single set of ultrasound images is marked as xs, the frame rate of the i-th patient in a single ultrasound examination is marked as zl, and the grayscale contrast of the i-th patient's single set of ultrasound images is marked as hd; In the formula, Represents the ratio of ultrasound frequency to ultrasound image spatial resolution, xs max and xs min are the maximum and minimum values ​​of the single group of ultrasound image pixels of the i-th patient, respectively, max -xs min represents the extreme difference of the pixel value of a single group of ultrasound images of the i-th patient, Represents the ratio of frame rate to grayscale contrast of ultrasound image, Jcsj i represents the detection data set Jcsj corresponding to a single ultrasound examination of the i-th patient i .

6. The ultrasound imaging-based thyroid nodule assessment system according to claim 5, characterized in that: The nodule volume TJ calculation process is as follows: According to the medical data set, the medical examination data of the i-th patient is extracted, and the transverse diameter of the nodule detected by CT scan of the i-th patient is marked as hj i , the longitudinal diameter of the nodule detected by CT scan of the i-th patient is marked as zj i ; TJ i =hj i ×z j In the formula, TJ i represents the nodule volume of the i-th patient.

7. The ultrasound imaging-based thyroid nodule assessment system according to claim 6, characterized in that: The nodule scoring Jep analysis process is as follows: If the number of nodules in the i-th patient is greater than 1, the nodule score of the i-th patient is Jep i Add 1; If the transverse diameter of the nodule of the i-th patient hj i Exceeding the length threshold CDY or the longitudinal diameter zj of the nodule of the i-th patient i When the longitudinal diameter threshold ZJY is exceeded, the nodule score Jep of the i-th patient i Add 1; If the nodule volume TJ of the i-th patient i When the volume threshold TJY is exceeded, the nodule score Jep of the i-th patient i Add 1; If the nodule morphology of the i-th patient is irregular, the nodule score of the i-th patient is Jep i Add 1; If the edge of the nodule of the i-th patient is blurred, the nodule score of the i-th patient is Jep i Add 1; If the echo intensity of the nodule of the i-th patient is lower than the intensity threshold QDY, the nodule score of the i-th patient is Jep i Add 1; If the echo intensity of the nodule of the i-th patient exceeds the intensity threshold QDY, the nodule score of the i-th patient Jep i Add 2; If the nodule of the i-th patient is irregular in shape and has blurred nodule margins, the nodule score of the i-th patient is Jep i Add 3; If the blood supply grade of the nodule of the i-th patient is higher than grade I, the nodule score of the i-th patient is Jep i Add 2.

8. The ultrasound imaging-based thyroid nodule assessment system according to claim 7, characterized in that: When the functional coefficient Gnx exceeds the functional threshold GNY, it indicates that the patient's thyroid function is abnormal and the corresponding risk level is low. It is recommended that the patient undergo an ultrasound examination in a timely manner.

9. The ultrasound imaging-based thyroid nodule assessment system according to claim 8, characterized in that: When the number of nodules is greater than 1 and the nodule score Jep is included in the score threshold JEPY, it means that the risk level corresponding to the patient's thyroid nodules is medium. The evaluation management unit screens ultrasound image key frames according to the detection data group Jcsj, and the screening process is as follows: If in the detection data set Jcsj, the ratio of the ultrasonic frequency to the ultrasonic image spatial resolution is included in the rate ratio threshold LBY, the ultrasonic image pixel value range is included in the range threshold JCY, and the ratio of the frame rate to the ultrasonic image grayscale contrast is included in the contrast threshold DBY, it means that the picture quality of the ultrasonic image is good, that is, it is a key frame.

10. The ultrasound imaging-based thyroid nodule assessment system according to claim 9, characterized in that: When the nodule score Jep exceeds the score threshold JEPY, it means that the risk level corresponding to the patient's thyroid nodule is high, and it is recommended to perform fine needle puncture examination in time.

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