Oral cavity auxiliary examination control system

Abstract

The invention relates to the technical field of oral cavity auxiliary examination control, in particular to an oral cavity auxiliary examination control system. Comprising a memory, an auxiliary detection control module and an output processing module, a three-dimensional oral cavity image is obtained through an oral cavity endoscope or CBCT equipment, the health state of the superficial layer and the structural layer of the oral cavity is analyzed in real time, and a preliminary auxiliary examination report of the superficial layer and the structural layer of the oral cavity is automatically generated; the report optimal value is obtained through comprehensive analysis of the report duration and the report abnormal value, and the emergency degree and the complexity degree of each auxiliary inspection report can be accurately evaluated; meanwhile, the diagnosis record of the oral doctor end and the current task load are deeply analyzed to obtain the corresponding processing value, the diagnosis level and the working efficiency of the doctor can be comprehensively evaluated, the dynamic adjustment of the processing value ensures the continuous optimization of the doctor, and the accurate matching to the proper doctor end is realized. Therefore, the overall efficiency and accuracy of oral examination are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oral cavity auxiliary inspection control, in particular to an oral cavity auxiliary inspection control system. Background Art

[0002] Oral auxiliary examination refers to the examination of the patient's oral health status with the help of various auxiliary equipment and technologies during the oral medical treatment process, so that the doctor can evaluate the patient's oral condition and formulate a treatment plan; it can be seen that the development of oral auxiliary examination technology has improved the early detection rate and diagnosis and treatment level of oral diseases, which is crucial to maintaining the patient's oral health; current oral auxiliary examinations are usually carried out manually with the help of auxiliary equipment, manual inspection and judgment, but this method greatly reduces work efficiency; and the manual inspection method will cause omissions in oral examinations due to different subjective consciousness of people. Summary of the invention

[0003] The purpose of the present invention is to provide an oral auxiliary inspection control system to solve the problems mentioned in the above background technology.

[0004] The object of the present invention can be achieved by the following technical solution: An oral auxiliary inspection control system, comprising: a memory, an auxiliary inspection control module and an output processing module;

[0005] The memory is connected to the oral examination device to acquire the user's three-dimensional oral image in real time and store it; each three-dimensional oral image is classified into the oral superficial layer and the oral structure layer according to its source;

[0006] The auxiliary inspection control module performs real-time analysis based on the user's three-dimensional oral image to preliminarily determine the state of the superficial layer and the structural layer of the oral cavity, and outputs an auxiliary inspection report based on this; the specific auxiliary inspection report includes a superficial layer auxiliary inspection report and a structural layer auxiliary inspection report; the auxiliary inspection report output process is as follows:

[0007] Step 1: If the category is the oral superficial layer, then step 2 will be executed; if the category is the oral structural layer, then step 3 will be executed;

[0008] Step 2: preliminarily judging the state of the superficial layer of the oral cavity based on the three-dimensional oral cavity image of the category of the superficial layer of the oral cavity, and outputting a superficial layer auxiliary inspection report; specifically, the superficial layer auxiliary inspection report is composed of the three-dimensional oral cavity image, the category, the superficial abnormality part and its corresponding superficial abnormality value, the local image and the position coordinates;

[0009] Step 3: Preliminarily judge the state of the oral structure layer based on the three-dimensional oral image of the oral structure layer category, and output the structure layer auxiliary inspection report; the structure layer auxiliary inspection report is composed of the three-dimensional oral image, the category, the structural abnormality area and its corresponding structural abnormality value, and the local image;

[0010] The output processing module matches the report based on the user's auxiliary examination report and sends it to the corresponding dentist.

[0011] Preferably, the state of the superficial layer of the oral cavity is preliminarily determined based on the three-dimensional oral image of the user, and the specific process is as follows: 2-1: extracting a three-dimensional oral cavity model of the superficial layer of the oral cavity, reconstructing it to obtain a three-dimensional surface model with a smooth surface; dividing the oral cavity into a plurality of parts according to the three-dimensional surface model, and generating a unique position coordinate according to the position of each part in the three-dimensional surface model, and meshing the three-dimensional surface model to form a plurality of surface points in each part;

[0012] 2-2: Calculate the curvature value of each surface point, and conduct a comprehensive quantitative analysis of the curvature change degree and curvature abnormality degree in each part to obtain the curvature performance value of each part;

[0013] 2-3: Identify the color of each surface point in each part and its category, specifically gums or teeth, and conduct a comprehensive quantitative analysis of the color abnormality and color change of each part to obtain the color expression value of each part;

[0014] 2-4: The curvature value K of each part Q And color representation value K Y The shallow outlier value QY is obtained by formula calculation and analysis. The specific calculation formula is:

[0015] QY=λ5×K Q +λ6×K Y

[0016] Among them, λ5 and λ6 are respectively set proportional constants; thereby, the superficial abnormality value of each part in the three-dimensional oral image can be obtained. If the superficial abnormality value is greater than or equal to the set superficial abnormality threshold, the part is recorded as a superficial abnormality part, and the local image here and its corresponding position coordinates are extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the superficial abnormality part and its corresponding superficial abnormality value, the local image and the position coordinates constitute the oral superficial layer auxiliary inspection report, and it is output.

[0017] Preferably, the specific process of conducting comprehensive quantitative analysis on the curvature variation degree and curvature abnormality degree in each part is as follows:

[0018] The curvature values ​​of two adjacent surface points are calculated by difference to obtain the curvature gradient value, thereby obtaining several curvature gradient values; assuming that there is a standard curvature gradient value, the curvature gradient value is compared with the standard curvature gradient value, if the curvature gradient value is greater than the standard curvature gradient value, the curvature gradient value is recorded as the abnormal curvature gradient value, the number of abnormal curvature gradient values ​​in the part is counted, and then the average of each abnormal curvature gradient value is calculated to obtain the abnormal curvature gradient mean; the number of abnormal curvature gradient values ​​and the abnormal curvature gradient mean are normalized and their values ​​are taken, and the values ​​are weighted to obtain the curvature gradient change value recorded as Q1;

[0019] It is assumed that there is a standard curvature interval, and the standard curvature interval of the curvature value of each surface point is compared with the standard curvature interval to determine the curvature abnormal point and its corresponding abnormal curvature value. The specific determination method is: if the curvature value of the surface point is greater than the upper limit of the standard curvature interval or less than the lower limit of the standard curvature interval, the surface point is recorded as a curvature abnormal point, and its curvature value is calculated by difference with the upper limit of the standard curvature interval and the lower limit of the standard curvature interval respectively, and the smallest difference is selected as the abnormal curvature value of the curvature abnormal point, and the curvature abnormal point is marked with a color different from the background color; the abnormal curvature values ​​corresponding to each curvature abnormal point are summed up to obtain the total abnormal curvature value recorded as Q2;

[0020] The curvature gradient change value Q1 and the total value of abnormal curvature Q2 are calculated and analyzed by formula to obtain the curvature performance value K Q The specific calculation formula is:

[0021] K Q =log2(λ1×e Q1 +λ2×e Q2 +1)

[0022] Wherein λ1 and λ2 are respectively set proportional constants, and their specific values ​​are set by those skilled in the art according to actual needs.

[0023] Preferably, the specific process of conducting comprehensive quantitative analysis on the degree of color abnormality and color change of each part is as follows:

[0024] The color of each surface point is represented as an RGB triplet using the RGB color model. The specific RGB triplet is represented as (Ri, Gi, Bi), where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of surface points, and i represents any one of the surface points; different categories of surface points are set to correspond to a standard color triplet, which is recorded as (HR, HG, HB), and the color difference value Di of each surface point is calculated in the RGB space by using the Euclidean distance. The specific Euclidean distance formula is:

[0025] It is assumed that there is a standard color difference value. If the color difference value is greater than the standard color difference value, the surface point is recorded as the color difference abnormal point, and the color difference value is used as the color difference abnormal value of the color difference abnormal point; then the color difference abnormal values ​​of each color difference abnormal point are summed up to obtain the total color difference abnormal value recorded as S1;

[0026] The color three elements of two adjacent surface points are calculated in the RGB space using the Euclidean distance to obtain the color gradient value of the two adjacent surface points with respect to the color three elements, thereby obtaining a number of color gradient values; a standard color gradient value is assumed to exist, and if the color gradient value is greater than the standard color gradient value, the color gradient value is recorded as an abnormal color gradient value, the number of abnormal color gradient values ​​is counted, and the average of each abnormal color gradient value is calculated to obtain the abnormal color gradient average; the number of abnormal color gradient values ​​and the abnormal color gradient average are normalized and their values ​​are taken, and the values ​​are weighted to obtain the abnormal color change value recorded as S2;

[0027] The color difference abnormal total value S1 and abnormal color change value S2 are calculated and analyzed by formula to obtain the color performance value K Y , the specific calculation formula is:

[0028] K Y =log2(λ3×e Y1 +λ4×e Y2 +1)

[0029] Among them, λ3 and λ4 are respectively set proportional constants, and their specific values ​​are set by those skilled in the art according to actual needs.

[0030] Preferably, the state of the oral structure layer is preliminarily determined based on the three-dimensional oral image of the user, and the specific process is as follows: 3-1: extracting a three-dimensional oral model of the oral structure layer, and dividing it into a plurality of regions according to the anatomical region division principle, wherein each tooth and its corresponding transmission area part, tooth root part and alveolar bone part are divided into one region, thereby obtaining a plurality of regions;

[0031] 3-2: Identify each area and extract the density value of the apical transmission area of ​​each tooth, the periodontal membrane thickness of the alveolar bone, and the alveolar bone distance, and record them as A, C, and V respectively; assume that there is a set of standard tooth three elements, which include a standard density interval, a standard periodontal membrane thickness interval, and a standard alveolar bone distance, and record them as [R1, R2], [R3, R4], and R5 respectively; The density value, periodontal membrane thickness, alveolar bone distance, standard density interval, standard periodontal membrane thickness interval, and standard alveolar bone distance of each tooth are calculated and analyzed by formula to obtain the apical expression value G of each tooth A , periodontal performance value G C and alveolar bone performance value G V, the specific calculation formula is:

[0032]

[0033] Wherein η1, η2, and η3 are respectively set proportional coefficients, and their values ​​are set by personnel in this field according to actual needs;

[0034] 3-3: The root apex expression value G A , periodontal performance value G C and alveolar bone performance value G V After normalization, the numerical value is taken and the numerical value is analyzed and calculated by formula to obtain the tooth structure abnormality value ACV. The specific calculation formula is:

[0035] ACV=δ1×G A +δ2×G C +δ3×G V

[0036] Among them, δ1, δ2, and δ3 are the set proportional coefficients respectively;

[0037] 3-4: Thus, the structural abnormality value of each tooth can be obtained. If the structural abnormality value is greater than or equal to the structural abnormality threshold, the tooth area is recorded as the structural abnormality area, and its local image is extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the structural abnormality area and its corresponding structural abnormality value, and the local image constitute a structural layer auxiliary inspection report, which is then output.

[0038] Preferably, the specific process of report matching based on the user's auxiliary examination report is as follows:

[0039] Step 1: Assume that there are several dentist terminals, and classify them into superficial categories and structural categories according to their areas of expertise; the superficial categories and structural categories correspond to several dentist terminals respectively; each dentist terminal corresponds to a processing value, and the dentist terminals of the same category are sorted in descending order according to their corresponding processing values, and the dentist terminal with the largest processing value is selected as the target terminal;

[0040] Step 2: Extract the report time from each auxiliary inspection report belonging to the same category, and calculate the time difference between it and the current time of the system to obtain the report time, and record it as P1; count the number of superficial abnormal parts or structural abnormal values ​​in each auxiliary inspection report, and sum up the corresponding superficial abnormal values ​​or structural abnormal values ​​to obtain the total value of superficial abnormalities or the total value of structural abnormalities as the report abnormality value, and record it as P2; normalize the report time P1 and the report abnormality value P2 and take their values, and perform formulaic calculation and analysis on the values ​​to obtain the report optimal value Pg. The specific calculation formula is:

[0041] Pg=g1×P1+g2×P2

[0042] Among them, g1 and g2 are the set proportional constants respectively;

[0043] Step 3: Sort the auxiliary examination reports of the same category in descending order according to their corresponding report preference values, and select the auxiliary examination report with the largest report preference value as the target report; assign the target report to the target doctor end of the same category, thereby increasing the number of reports in the processing list of the dentist end by one; whenever the dentist end completes a report diagnosis, the number of reports in the corresponding processing list decreases by one, and the diagnostic parameters of this report diagnosis are recorded at the same time, and the specific diagnostic parameters include the diagnosis start time and the diagnosis end time;

[0044] Step 4: Each time a report diagnosis is completed, a cumulative analysis of the diagnosis is performed to obtain the latest processing value on the dentist's side, and it is updated to step 1; specifically:

[0045] Step 5: Repeat steps 1 to 4 above until all the auxiliary examination reports are diagnosed and processed.

[0046] Preferably, the specific process of diagnostic cumulative analysis is:

[0047] Count the number of reported diagnoses. If the number of reported diagnoses is zero, the processing value is assigned to M.

[0048] If the number of reported diagnoses is greater than zero, a cumulative diagnosis analysis is performed, specifically:

[0049] Extract the historical diagnosis times of each dentist in the same category, as well as the start and end time of each diagnosis, and calculate the difference between them to get the duration of each diagnosis. Calculate the average duration of each diagnosis to get the average duration of diagnosis, which is recorded as Z1.

[0050] Obtain feedback records from the dentist, where the feedback records include the number of feedbacks and feedback evaluations. Each feedback is divided into satisfactory feedback and unsatisfactory feedback according to the feedback evaluation. The number of satisfactory feedback and unsatisfactory feedback is counted respectively, and they are recorded as Z2 and Z3 respectively.

[0051] Get the number of reports in the processing list of the dentist at the current time and record it as Z4;

[0052] The average diagnosis length Z1, the number of satisfactory feedback Z2, the number of unsatisfactory feedback Z3 ​​and the number of reports Z4 are normalized and their values ​​are taken. The values ​​are analyzed and calculated by formula to obtain the processing value Zβ. The specific calculation formula is:

[0053]

[0054] Among them, β1, β2, β3, and β4 are the set proportional constants respectively.

[0055] Beneficial effects of the present invention:

[0056] 1. Through the three-dimensional oral images obtained by oral endoscope or CBCT equipment, the health status of the superficial layer and structural layer of the oral cavity is analyzed in real time, and possible oral abnormalities are automatically evaluated, which reduces the workload of doctors and improves the efficiency of examination. The preliminary auxiliary examination report of the superficial layer and structural layer of the oral cavity is automatically generated, which can effectively assist the dentist in the examination. Compared with the traditional manual diagnosis, it reduces the workload of the doctor, avoids human errors, and ensures the high accuracy of the diagnosis results. 2. Through image annotation, local image extraction and other methods, it helps doctors better understand the image information, provides a clearer view, and enhances decision support. Doctors can quickly locate abnormal areas according to the report, providing auxiliary functions for dentists.

[0057] 3. The optimal report value is obtained through comprehensive analysis of report duration and report abnormal values, which can accurately evaluate the urgency and complexity of each auxiliary examination report, ensuring that urgent and complex reports can be processed as a priority to avoid delays or omissions; at the same time, through in-depth analysis of the diagnosis records and current task volume on the dentist's side, the corresponding processing value is obtained, which can comprehensively evaluate the doctor's diagnostic level and work efficiency. The dynamic adjustment of the processing value ensures the continuous optimization of the doctor, which not only improves the diagnostic efficiency, but also ensures the best use of resources, and achieves accurate matching to the appropriate doctor, thereby improving the overall efficiency and accuracy of oral examinations. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention will be further described below in conjunction with the accompanying drawings.

[0059] Figure 1 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 creative work are within the scope of protection of the present invention.

[0061] See also Figure 1 As shown, the present invention is an oral auxiliary inspection control system, comprising: a memory, an auxiliary inspection control module and an output processing module;

[0062] The memory is connected by communicating with an oral examination device (usually an endoscope or CBCT, etc.) to acquire a three-dimensional oral image of the user in real time and store it; specifically, an oral endoscope is used for image acquisition to generate a number of two-dimensional oral images, which are then stitched together by an algorithm to obtain a three-dimensional oral image of the user; or, a CBCT (cone beam CT) is used to perform a full-mouth scan of the user to obtain a three-dimensional oral image of the user; it should be noted that if the user needs to check local oral problems (such as gingivitis, caries, tartar, etc.), the oral examination device commonly used is an endoscope, which is mainly used to examine the user's superficial oral layer; if the user needs to check complex oral diseases (such as periodontal disease, root lesions, tooth displacement, jaw lesions, etc.), the oral examination device commonly used is CBCT (cone beam CT), which is mainly used to examine the user's oral structural layer; thus, each three-dimensional oral image can be classified into the superficial oral layer and the oral structural layer according to its source.

[0063] The auxiliary inspection control module performs real-time analysis based on the user's three-dimensional oral image to preliminarily determine the state of the oral superficial layer and the oral structure layer, and outputs an auxiliary inspection report based on this; specifically:

[0064] Step 1: If the category is the oral superficial layer, then step 2 will be executed; if the category is the oral structural layer, then step 3 will be executed;

[0065] Step 2: Preliminary judgment of the superficial state of the oral cavity, specifically:

[0066] 2-1: Extract the three-dimensional oral model of the superficial layer of the oral cavity, reconstruct it and convert it into a three-dimensional surface model with a smooth surface; divide the oral cavity into several parts according to the three-dimensional surface model (usually when dividing the parts, the gum part and the tooth part are separated; for example, a certain part is a small part of the gum, and a certain part is a small part of the tooth), and generate a unique position coordinate according to the position of each part in the three-dimensional surface model to represent its position in the three-dimensional surface model, and grid the three-dimensional surface model to ensure that the spatial position and normal information of each surface point in the part are available; 2-2: Calculate the curvature value of each surface point. It should be noted that problems such as caries, tartar, and gingivitis are usually manifested as depressions, missing parts, or protrusions with large local curvatures; The curvature values ​​of two adjacent surface points are calculated by difference to obtain the curvature gradient value, thereby obtaining several curvature gradient values; It is assumed that there is a standard curvature gradient value (The standard curvature gradient value refers to the curvature change performance of a normal oral cavity, and its specific value is set by technical personnel in this field based on their own work experience), the curvature gradient value is compared with the standard curvature gradient value, if the curvature gradient value is greater than the standard curvature gradient value, it indicates that the curvature change is abnormal, and the possibility of the existence of superficial oral abnormalities is greater; the curvature gradient value is recorded as the abnormal curvature gradient value, the number of abnormal curvature gradient values ​​in the part is counted, and then the average of each abnormal curvature gradient value is calculated to obtain the abnormal curvature gradient average; the number of abnormal curvature gradient values ​​and the abnormal curvature gradient average are normalized and their values ​​are taken, and the values ​​are weighted to obtain the curvature gradient change value recorded as Q1; it is not difficult to know from the calculation of the curvature gradient change value that the more abnormal curvature gradient values ​​in the part, the larger the abnormal curvature gradient average, the more serious the abnormal curvature change in the part, and the greater the possibility of the existence of superficial oral abnormalities, and the larger the curvature gradient change value;

[0067] It is assumed that there is a standard curvature interval (the standard curvature interval refers to the curvature performance of a normal oral cavity, and its specific value is set by technicians in this field based on their own work experience). The standard curvature interval of the curvature value of each surface point is compared with the standard curvature interval to determine the curvature abnormal point and its corresponding abnormal curvature value. The specific determination method is: if the curvature value of the surface point is greater than the upper limit of the standard curvature interval or less than the lower limit of the standard curvature interval, the surface point is recorded as a curvature abnormal point, and its curvature value is calculated by difference with the upper limit of the standard curvature interval and the lower limit of the standard curvature interval respectively, and the smallest difference is selected as the abnormal curvature value of the curvature abnormal point, and the curvature abnormal point is marked with a color different from the background color; the abnormal curvature values ​​corresponding to each curvature abnormal point are summed to obtain the total abnormal curvature value, and it is recorded as Q2;

[0068] The curvature gradient change value Q1 and the total value of abnormal curvature Q2 are calculated and analyzed by formula to obtain the curvature performance value KQ The specific calculation formula is:

[0069] K Q =log2(λ1×e Q1 +λ2×e Q2 +1)

[0070] Among them, λ1 and λ2 are respectively set proportional constants, and their specific values ​​are set by the personnel in this field according to actual needs; it can be seen from the formula that the larger the curvature gradient change value, the larger the total value of abnormal curvature, which means that the possibility of superficial oral abnormalities in this part is greater, and the curvature expression value is greater; it should be noted that the surface curvature of normal teeth is smooth and continuous, and the curve of healthy gums is smooth and fits the teeth; therefore, the abnormal curvature change means that the possibility of superficial oral abnormalities is greater; 2-3: Identify the color of each surface point in each part and its category (specific category is gums or teeth), and use the RGB color model to The color of each surface point is represented by an RGB triplet, specifically (Ri, Gi, Bi), where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of surface points, and i represents any one of the surface points; different categories of surface points are set to correspond to a standard color triplet, and it is recorded as (HR, HG, HB), for example, the color corresponding to the standard color triplet of gums is light pink, and the color corresponding to the standard color triplet of teeth is white; it should be noted that the color difference value Di of each surface point is calculated in the RGB space by using the Euclidean distance, and the specific Euclidean distance formula is:

[0071] It is assumed that there is a standard color difference value (the standard color difference value refers to the allowable range of normal gum or normal tooth color, and its value is set by technicians in this field based on their own work experience), and the color difference value of each surface point is compared and analyzed with the standard color difference value. If the color difference value is greater than the standard color difference value, the surface point is recorded as a color difference abnormal point, and the color difference value is used as the color difference abnormal value of the color difference abnormal point; then the color difference abnormal values ​​of each color difference abnormal point are summed up to obtain a total color difference abnormal value recorded as S1;

[0072] The color three elements of two adjacent surface points are calculated in RGB space using Euclidean distance to obtain the color gradient value of the two adjacent surface points with respect to the color three elements, thereby obtaining a number of color gradient values, which represent the color change degree value of the two adjacent surface points; a standard color gradient value is assumed to exist (the standard color gradient value refers to the color change performance of a normal oral cavity, and its value is set by a technician in this field based on their own work experience), and each color gradient value is compared with the standard color gradient value. If the color gradient value is greater than the standard color gradient value, indicating that the color change is abnormal, the color gradient value is recorded as an abnormal color gradient value, the number of abnormal color gradient values ​​is counted, and the average of each abnormal color gradient value is calculated to obtain an abnormal color gradient average; the number of abnormal color gradient values ​​and the abnormal color gradient average are normalized and their values ​​are taken, and the values ​​are weighted to obtain an abnormal color change value recorded as S2;

[0073] The color difference abnormal total value S1 and abnormal color change value S2 are calculated and analyzed by formula to obtain the color performance value K Y , the specific calculation formula is:

[0074] K Y =log2(λ3×e Y1 +λ4×e Y2 +1)

[0075] Among them, λ3 and λ4 are respectively set proportional constants, and their values ​​are set by the personnel in this field according to actual needs. It can be seen from the formula that when the color in the user's three-dimensional oral image is more different from the standard color, and the color change of the same type of position is greater, it means that there is a greater possibility of superficial abnormality in the oral cavity, and the color expression value is greater; 2-4: The curvature expression value K of each part Q And color representation value K Y The shallow outlier value QY is obtained by formula calculation and analysis. The specific calculation formula is:

[0076] QY=λ5×K Q +λ6×K Y

[0077] Wherein λ5 and λ6 are respectively set proportional constants; thereby, the superficial abnormality value of each part in the three-dimensional oral image can be obtained, and the superficial abnormality value is compared and analyzed with the set superficial abnormality threshold value; if the superficial abnormality value is greater than or equal to the set superficial abnormality threshold value, the part is recorded as a superficial abnormal part, and the local image and its corresponding position coordinates are extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the superficial abnormal part and its corresponding superficial abnormality value, the local image and the position coordinates constitute a superficial auxiliary inspection report, and it is output;

[0078] Step 3: Preliminary judgment of the state of the oral structure layer, specifically:

[0079] 3-1: Extract the three-dimensional oral cavity model of the oral structure layer, and divide it into several regions according to the anatomical region division principle, wherein each tooth and its corresponding transmission area, root part and alveolar bone part are divided into one region, thereby obtaining several regions;

[0080] 3-2: Identify each area and extract the density value of the apical radiolucency zone of each tooth (normal apical radiolucency zone density is usually 400-1000HU. If it is lower than 400HU, there is a risk of apical lesions or bone resorption problems), the thickness of the periodontal ligament of the alveolar bone (normal periodontal ligament thickness is 0.2-0.4mm. If the apical periodontal ligament thickness exceeds 0.4mm, it indicates the risk of apical inflammation or periodontitis; if it is less than 0.2mm, it means that the density of the tooth root is close to that of the alveolar bone, the periodontal ligament disappears or becomes thinner, and there is a risk of periodontal ligament atrophy, adhesion or sclerosis), and the alveolar bone distance (the alveolar bone distance refers to the vertical distance from the top of the alveolar bone to the bifurcation point of the tooth root. Normally, the normal alveolar bone distance is 1-2mm , greater than 2mm indicates the presence of alveolar bone resorption, i.e., the risk of periodontal disease), and they are recorded as A, C, and V respectively; a set of three standard tooth elements is assumed, including a standard density interval, a standard periodontal membrane thickness interval, and a standard alveolar bone distance, and they are recorded as [R1, R2], [R3, R4], and R5 respectively; it should be noted that usually R1 is 400HU, R2 is 1000HU, R3 is 0.2mm, R4 is 0.4mm, and R5 is 2mm; the density value, periodontal membrane thickness, alveolar bone distance, standard density interval, standard periodontal membrane thickness interval, and standard alveolar bone distance of each tooth are calculated and analyzed by formula to obtain the root apex performance value G of each tooth A , periodontal performance value G C and alveolar bone performance value G V , the specific calculation formula is:

[0081]

[0082] Wherein η1, η2, η3 are respectively set proportional coefficients, and their values ​​are set by the personnel in this field according to actual needs; min{A-[R1, R2]} means that A is calculated by difference with R1 and R2 respectively, and the smallest difference is selected; min{C-[R3, R4]}min{A-[R1, R2]} means that C is calculated by difference with R3 and R4 respectively, and the smallest difference is selected;

[0083] 3-3: The root apex expression value G A , periodontal performance value G C and alveolar bone performance value G VAfter normalization, the numerical value is taken and the numerical value is analyzed and calculated by formula to obtain the tooth structure abnormality value ACV. The specific calculation formula is:

[0084] ACV=δ1×G A +δ2×G C +δ3×G V

[0085] Among them, δ1, δ2, and δ3 are the set proportional coefficients. It can be seen from the formula that when the root apex performance value G A The larger the periodontal performance value G C The larger the alveolar bone performance value G V The larger it is, the greater the risk of having an abnormality in the oral structure layer, and the larger the structural abnormality value;

[0086] 3-4: Thus, the structural abnormality value of each tooth can be obtained, and it is compared and analyzed with the set structural abnormality threshold. If the structural abnormality value is greater than or equal to the structural abnormality threshold, the tooth area is recorded as a structural abnormality area, and its local image is extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the structural abnormality area and its corresponding structural abnormality value, and the local image constitute a structural layer auxiliary inspection report, and it is output;

[0087] Sending the shallow layer auxiliary inspection report and the structural layer auxiliary inspection report to the output processing module;

[0088] The three-dimensional oral images obtained by oral endoscope or CBCT equipment can analyze the health status of the superficial and structural layers of the oral cavity in real time, automatically evaluate possible oral abnormalities, reduce the workload of doctors, and improve inspection efficiency; automatically generate preliminary auxiliary inspection reports of the superficial and structural layers of the oral cavity, which can effectively assist dentists in inspections; compared with traditional manual diagnosis, it reduces the workload of doctors and avoids human errors, ensuring the high accuracy of diagnostic results; at the same time, through image annotation, local image extraction and other methods, it helps doctors better understand image information, provides clearer views, and enhances decision support. Doctors can quickly locate abnormal areas based on the report, providing assistance to dentists. The output processing module matches the user's auxiliary inspection report (including the superficial auxiliary inspection report and the structural layer auxiliary inspection report) and sends it to the corresponding doctor end to achieve the goal of improving the efficiency and accuracy of the user's oral inspection; specifically:

[0089] Step 1: Assume that there are several dentist terminals, and classify them according to their expertise, into superficial categories and structural categories. The specific classification is made by personnel in this field according to the expertise of each dentist; the superficial category and the structural category correspond to several dentist terminals respectively, each dentist terminal corresponds to a processing value, obtain the latest processing value, and sort the dentist terminals of the same category in order from large to small according to their corresponding processing values, and select the dentist terminal with the largest processing value as the target terminal;

[0090] Step 2: Extract the report time (report time refers to the time when the user's report is generated) from each auxiliary inspection report belonging to the same category, and calculate the time difference between it and the current time of the system to obtain the report time, and record it as P1; count the number of superficial abnormal parts or structural abnormal values ​​in each auxiliary inspection report, and sum up the corresponding superficial abnormal values ​​or structural abnormal values ​​to obtain the total value of superficial abnormalities or the total value of structural abnormalities as the report abnormality value, and record it as P2; normalize the report time P1 and the report abnormality value P2 and take their values, and perform formulaic calculation and analysis on the values ​​to obtain the report optimal value Pg. The specific calculation formula is:

[0091] Pg=g1×P1+g2×P2

[0092] Among them, g1 and g2 are respectively set proportional constants. It can be seen from the formula that when the report duration is longer, it means that the report demand is given priority, and the corresponding report preference value is larger; when the report abnormality value is larger, it means that the report demand is given priority, and the corresponding report preference value is larger; thus, the report preference value of each auxiliary inspection report can be obtained;

[0093] Step 3: Sort the auxiliary examination reports of the same category in descending order according to their corresponding report preference values, and select the auxiliary examination report with the largest report preference value as the target report; assign the target report to the target doctor end of the same category, thereby increasing the number of reports in the processing list of the dentist end by one; whenever the dentist end completes a report diagnosis, the number of reports in the corresponding processing list decreases by one, and the diagnostic parameters of this report diagnosis are recorded at the same time, and the specific diagnostic parameters include the diagnosis start time and the diagnosis end time;

[0094] Step 4: Each time a report diagnosis is completed, a cumulative analysis of the diagnosis is performed to obtain the latest processing value on the dentist's side, specifically:

[0095] The number of reported diagnoses is counted. If the number of reported diagnoses is zero, the processing value is assigned to M (M is a fixed value, and the specific value is set by the personnel in this field. Usually, the personnel in this field will set it to two-thirds of the current dentist-side processing value ranking table of the same category);

[0096] If the number of reported diagnoses is greater than zero, a cumulative diagnosis analysis is performed, specifically:

[0097] Extract the historical diagnosis times of each dentist in the same category, as well as the start and end time of each diagnosis, and calculate the difference between them to get the duration of each diagnosis. Calculate the average duration of each diagnosis to get the average duration of diagnosis, which is recorded as Z1.

[0098] Obtain feedback records from the dentist, where the feedback records include the number of feedbacks and feedback evaluations. It should be noted that when the user undergoes an oral examination and subsequent oral diagnosis, the user provides feedback to the dentist after the diagnosis is completed. Usually, the number of feedbacks is less than the actual number of diagnoses by the dentist, because not all users will provide feedback after the diagnosis is completed; each feedback is divided into satisfactory feedback and unsatisfactory feedback according to the feedback evaluation, and the number of satisfactory feedback and unsatisfactory feedback are counted respectively, and recorded as Z2 and Z3 respectively;

[0099] Get the number of reports in the processing list of the dentist at the current time and record it as Z4;

[0100] The average diagnosis length Z1, the number of satisfactory feedback Z2, the number of unsatisfactory feedback Z3 ​​and the number of reports Z4 are normalized and their values ​​are taken. The values ​​are analyzed and calculated by formula to obtain the processing value Zβ. The specific calculation formula is:

[0101]

[0102] Among them, β1, β2, β3, and β4 are respectively the set proportional constants. It can be seen from the formula that when the average length of diagnosis is larger, it means that the efficiency of the dentist is lower, and the processing value is smaller; when the number of satisfactory feedbacks is larger and the number of unsatisfactory feedbacks is smaller, the processing value is larger; the larger the number of reports in the processing list, the smaller the processing value;

[0103] Update the processing values ​​of each dentist's end of the same category to step 1;

[0104] Step 5: Repeat steps 1 to 4 above until all the auxiliary examination reports are diagnosed and processed;

[0105] By comprehensively analyzing the report duration and report abnormal values ​​to obtain the report optimization value, the urgency and complexity of each auxiliary examination report can be accurately evaluated, ensuring that urgent and complex reports are processed as a priority to avoid delays or omissions. At the same time, through in-depth analysis of the dentist's diagnosis records and current task volume, the corresponding processing value can be obtained, which can comprehensively evaluate the doctor's diagnostic level and work efficiency. The dynamic adjustment of the processing value ensures the continuous optimization of the doctor, which not only improves the diagnostic efficiency, but also ensures the best use of resources, and achieves accurate matching to the appropriate doctor, thereby improving the overall efficiency and accuracy of oral examinations.

[0106] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An oral auxiliary inspection control system, characterized in that: include: Memory, auxiliary inspection control module and output processing module; The memory is connected to the oral examination device to acquire the user's three-dimensional oral image in real time and store it; Classify each three-dimensional oral cavity image into the oral superficial layer and the oral structure layer according to its source; The auxiliary inspection control module performs real-time analysis based on the user's three-dimensional oral image to preliminarily determine the state of the oral superficial layer and the oral structure layer, and outputs an auxiliary inspection report accordingly; The specific auxiliary inspection reports include the superficial layer auxiliary inspection report and the structural layer auxiliary inspection report; the auxiliary inspection report output process is as follows: Step 1: If the category is the oral superficial layer, then step 2 will be executed; if the category is the oral structural layer, then step 3 will be executed; Step 2: preliminarily judging the state of the superficial layer of the oral cavity based on the three-dimensional oral cavity image of the category of the superficial layer of the oral cavity, and outputting a superficial layer auxiliary inspection report; specifically, the superficial layer auxiliary inspection report is composed of the three-dimensional oral cavity image, the category, the superficial abnormality part and its corresponding superficial abnormality value, the local image and the position coordinates; Step 3: Preliminarily judge the state of the oral structure layer based on the three-dimensional oral image of the oral structure layer category, and output the structure layer auxiliary inspection report; the structure layer auxiliary inspection report is composed of the three-dimensional oral image, the category, the structural abnormality area and its corresponding structural abnormality value, and the local image; The output processing module matches the report based on the user's auxiliary examination report and sends it to the corresponding dentist.

2. The oral auxiliary inspection control system according to claim 1, characterized in that: The superficial state of the oral cavity is preliminarily judged based on the user's three-dimensional oral image. The specific process is as follows: 2-1: Extract the three-dimensional oral model of the superficial layer of the oral cavity, reconstruct it and convert it into a three-dimensional surface model with a smooth surface; divide the oral cavity into several parts according to the three-dimensional surface model, and generate a unique position coordinate according to the position of each part in the three-dimensional surface model, and mesh the three-dimensional surface model to form several surface points in each part; 2-2: Calculate the curvature value of each surface point, and conduct a comprehensive quantitative analysis of the curvature change degree and curvature abnormality degree in each part to obtain the curvature performance value of each part; 2-3: Identify the color of each surface point in each part and its category, the specific category is gums or teeth, and conduct a comprehensive quantitative analysis of the color abnormality and color change degree of each part to obtain the color expression value of each part; 2-4: Formulate and analyze the curvature expression value and color expression value of each part to obtain the superficial abnormality value; thereby, the superficial abnormality value of each part in the three-dimensional oral image can be obtained. If the superficial abnormality value is greater than or equal to the set superficial abnormality threshold, the part is recorded as a superficial abnormality part, and the local image here and its corresponding position coordinates are extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the superficial abnormality part and its corresponding superficial abnormality value, the local image and the position coordinates constitute the oral superficial layer auxiliary inspection report, and it is output.

3. The oral auxiliary inspection control system according to claim 2, characterized in that: The specific process of comprehensive quantitative analysis of the curvature change degree and curvature abnormality degree in each part is as follows: The curvature values ​​of two adjacent surface points are calculated by difference to obtain the curvature gradient value, thereby obtaining several curvature gradient values; assuming that there is a standard curvature gradient value, the curvature gradient value is compared with the standard curvature gradient value, if the curvature gradient value is greater than the standard curvature gradient value, the curvature gradient value is recorded as an abnormal curvature gradient value, the number of abnormal curvature gradient values ​​in the part is counted, and then the average of each abnormal curvature gradient value is calculated to obtain the average value of the abnormal curvature gradient; The number of abnormal curvature gradient values ​​and the mean value of the abnormal curvature gradient are normalized and their values ​​are taken, and the values ​​are weighted to obtain the curvature gradient change value; a standard curvature interval is set, and the standard curvature interval of the curvature value of each surface point is compared with the standard curvature interval to determine the curvature abnormal point and its corresponding abnormal curvature value. The specific determination method is: if the curvature value of the surface point is greater than the upper limit of the standard curvature interval or less than the lower limit of the standard curvature interval, the surface point is recorded as a curvature abnormal point, and its curvature value is calculated by difference with the upper limit of the standard curvature interval and the lower limit of the standard curvature interval respectively, and the smallest difference is selected as the abnormal curvature value of the curvature abnormal point, and the curvature abnormal point is marked with a color different from the background color; The abnormal curvature values ​​corresponding to each abnormal curvature point are summed up to obtain the total abnormal curvature value; The curvature performance value is obtained by formulating and analyzing the curvature gradient change value and the total value of abnormal curvature.

4. The oral auxiliary inspection control system according to claim 3, characterized in that: The specific process of comprehensive quantitative analysis of the degree of color abnormality and color change of each part is as follows: The color of each surface point is represented as an RGB triplet using the RGB color model. The specific RGB triplet is represented as (Ri, Gi, Bi), where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of surface points, and i represents any one of the surface points; different categories of surface points are set to correspond to a standard color triplet, which is recorded as (HR, HG, HB), and the color difference value Di of each surface point is calculated in the RGB space by using the Euclidean distance. The specific Euclidean distance formula is: It is assumed that there is a standard color difference value. If the color difference value is greater than the standard color difference value, the surface point is recorded as a color difference abnormal point, and the color difference value is used as the color difference abnormal value of the color difference abnormal point; then the color difference abnormal values ​​of each color difference abnormal point are summed up to obtain the total color difference abnormal value; The color three elements of two adjacent surface points are calculated in RGB space using Euclidean distance to obtain the color gradient value of the two adjacent surface points with respect to the color three elements, thereby obtaining a number of color gradient values; a standard color gradient value is assumed to exist, and if the color gradient value is greater than the standard color gradient value, the color gradient value is recorded as an abnormal color gradient value, the number of abnormal color gradient values ​​is counted, and the average of each abnormal color gradient value is calculated to obtain the abnormal color gradient average; the number of abnormal color gradient values ​​and the abnormal color gradient average are normalized and their values ​​are taken, and the values ​​are weighted to obtain the abnormal color change value; The color performance value is obtained by formulating and analyzing the total color difference abnormality value and the abnormal color change value.

5. The oral auxiliary inspection control system according to claim 1, characterized in that: The state of the oral structure layer is preliminarily judged based on the user's three-dimensional oral image. The specific process is as follows: 3-1: Extract the three-dimensional oral cavity model of the oral structure layer, and divide it into several regions according to the anatomical region division principle, wherein each tooth and its corresponding transmission area, root part and alveolar bone part are divided into one region, thereby obtaining several regions; 3-2: Identify each area and extract the density value of the apical transmission area of ​​each tooth, the periodontal membrane thickness of the alveolar bone, and the alveolar bone distance; assume that there is a set of standard tooth three elements, which include a standard density interval, a standard periodontal membrane thickness interval, and a standard alveolar bone distance; perform formula calculation and analysis on the density value, periodontal membrane thickness, alveolar bone distance, standard density interval, standard periodontal membrane thickness interval, and standard alveolar bone distance of each tooth to obtain the apical expression value, periodontal expression value, and alveolar bone expression value of each tooth; 3-3: Normalize the root apex value, periodontal value and alveolar bone value and take their numerical values, and perform formula calculation and analysis on the numerical values ​​to obtain the structural abnormality value of the tooth; 3-4: Thus, the structural abnormality value of each tooth can be obtained. If the structural abnormality value is greater than or equal to the structural abnormality threshold, the tooth area is recorded as the structural abnormality area, and its local image is extracted from the three-dimensional oral image; the three-dimensional oral image, the category, the structural abnormality area and its corresponding structural abnormality value, and the local image constitute a structural layer auxiliary inspection report, which is then output.

6. The oral auxiliary inspection control system according to claim 1, characterized in that: The specific process of report matching based on the user's auxiliary examination report is as follows: Step 1: Assume that there are several dentist terminals, and classify them into superficial categories and structural categories according to their areas of expertise; the superficial categories and structural categories correspond to several dentist terminals respectively; each dentist terminal corresponds to a processing value, and the dentist terminals of the same category are sorted in descending order according to their corresponding processing values, and the dentist terminal with the largest processing value is selected as the target terminal; Step 2: Extract the report time from each auxiliary inspection report belonging to the same category, and calculate the time difference between it and the current time of the system to obtain the report duration; The number of superficial abnormal parts or structural abnormal values ​​in each auxiliary examination report is counted, and the corresponding superficial abnormal values ​​or structural abnormal values ​​are summed up to obtain the total superficial abnormality value or the total structural abnormality value as the report abnormality value; the report duration and the report abnormality value are normalized and their values ​​are taken, and the numerical values ​​are calculated and analyzed by formula to obtain the report optimal value; thus, the report optimal value of each auxiliary examination report can be obtained; Step 3: Sort the auxiliary examination reports of the same category in descending order according to their corresponding report preference values, and select the auxiliary examination report with the largest report preference value as the target report; assign the target report to the target doctor end of the same category, thereby increasing the number of reports in the processing list of the dentist end by one; whenever the dentist end completes a report diagnosis, the number of reports in the corresponding processing list decreases by one, and the diagnostic parameters of this report diagnosis are recorded at the same time, and the specific diagnostic parameters include the diagnosis start time and the diagnosis end time; Step 4: Each time a report diagnosis is completed, a cumulative analysis of the diagnosis is performed to obtain the latest processing value on the dentist's side, and it is updated to step 1; specifically: Step 5: Repeat steps 1 to 4 above until all the auxiliary examination reports are diagnosed and processed.

7. The oral auxiliary inspection control system according to claim 6, characterized in that: The specific process of diagnostic cumulative analysis is as follows: Count the number of reported diagnoses. If the number of reported diagnoses is zero, the processing value is assigned to M. If the number of reported diagnoses is greater than zero, a cumulative diagnosis analysis is performed, specifically: Extract the historical diagnosis times of each dentist in the same category, as well as the start and end times of each diagnosis, and calculate the difference in duration to obtain the duration of each diagnosis. Calculate the average duration of each diagnosis to obtain the average duration of the diagnosis. Obtain feedback records from the dentist, where the feedback records include the number of feedbacks and feedback evaluations. Each feedback is divided into satisfactory feedback and unsatisfactory feedback according to the feedback evaluation, and the number of satisfactory feedback and unsatisfactory feedback is counted respectively; Get the number of reports in the processing list of the dentist at the current time; The average length of diagnosis, the number of satisfactory feedbacks, the number of unsatisfactory feedbacks and the number of reports were normalized and their values ​​were taken, and the numerical values ​​were calculated and analyzed by formula to obtain the processed values.

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