CN115156087A - Denture sorting assisting method and device, computer equipment and readable storage medium - Google Patents
Denture sorting assisting method and device, computer equipment and readable storage medium Download PDFInfo
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Abstract
The invention provides a false tooth sorting auxiliary method, which comprises the steps of calculating to obtain the predicted sintered weight of each false tooth according to the volume data of an artificial tooth model of each false tooth and corresponding false tooth parameter data; after each denture is placed into the same sintering furnace for sintering, the actual sintered weight of each denture is obtained; determining candidate denture order data corresponding to each denture based on the predicted post-sintering weight and the actual post-sintering weight of each denture; determining target denture order data for each denture from the candidate denture order data for each denture to enable sorting of each denture; according to the embodiment of the invention, the sintered weight of the false tooth is intelligently predicted through the algorithm, and is rapidly compared with the actual sintered weight of the false tooth, so that a user can be assisted to rapidly sort the false tooth, and the sorting efficiency is effectively improved; the false tooth volume data and the false tooth parameter data are combined to predict the sintered weight of the false tooth and sort the false tooth, so that the false tooth sorting accuracy can be improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of dental restoration, in particular to a false tooth sorting assisting method, a false tooth sorting assisting device, false tooth sorting assisting computer equipment and a computer-readable storage medium.
Background
The materials of the false teeth which are widely used clinically at present are zirconia and glass ceramics, and the zirconia occupies most of the false teeth due to the advantages of high hardness, difficult deformation and the like. Wherein, after the zirconia false tooth is cut, the quality of the finished product tooth can be achieved only by sintering, and the zirconia sintering generally needs 8-10 hours. Because of the demands of denture manufacturing amount, existing denture manufacturers generally put a plurality of dentures into the same sintering furnace for simultaneous sintering, and sort the dentures after the denture sintering is completed. Except for a certain degree of identification of a dental bridge (a plurality of connected teeth), the shapes of other teeth are not very different, so that the sintered denture and a dental model of a patient can only be tried on one by one to find an order (or a dental box) where the teeth are located. However, the above method of trying to sort each denture one by one has the following drawbacks: and (1) the sorting takes long time and the sorting efficiency is low. Taking the example of sintering 30 dentures at one time, the first denture needs to be worn at most 30 times, the second denture needs to be worn at most 29 times, and so on, the 30 dentures need to be worn at most 30+29+28+27+. + -. 1=465 times, and the sorting efficiency is low; (2) Because the shape difference of some false teeth is very small, the situation that a plurality of false teeth can correctly wear the dental model often appears, so that the judgment needs to be carried out by depending on the professional of an operator, the error probability is higher, the accuracy is poor, and the requirement on the professional of the operator is high.
Disclosure of Invention
In view of this, embodiments of the present invention provide a denture sorting assisting method, a denture sorting assisting apparatus, a denture sorting computer device, and a computer-readable storage medium, which are used to solve the problems of low sorting efficiency and low accuracy of the existing denture sorting method.
The embodiment of the invention solves the technical problems through the following technical scheme:
one aspect of the present invention provides a denture sorting assisting method applied to a denture sorting assisting system, where the denture sorting assisting system includes a user side and a server side, and the user side includes a front end and a back end, and the method includes:
receiving, by the back end, denture model data and corresponding denture parameter data corresponding to at least one denture sent by the front end, wherein the denture model data and the denture parameter data are data obtained by the front end based on a user's operation on a preset region of the front end;
calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture through the rear end;
calculating to obtain the predicted sintered weight of each denture through the back end according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to the server;
after each denture is placed into the same sintering furnace for sintering, acquiring the actual sintered weight of each denture through the rear end, and sending the actual sintered weight of each denture to the server;
receiving, by the server, the predicted post-sinter weight and the actual post-sinter weight of the each denture, determining at least one candidate denture order data corresponding to the each denture based on the predicted post-sinter weight and the actual post-sinter weight of the each denture, and sending the at least one candidate denture order data corresponding to the each denture to the backend; and
determining, by the back end, a target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture, according to the received at least one candidate denture order data corresponding to each denture, to achieve a sorting of each denture.
Optionally, the obtaining, by the back end, denture model volume data corresponding to each denture by calculation according to the denture model data of each denture includes:
determining model vertex data for each denture from the denture model data for each denture by the back end;
segmenting each denture through the rear end according to the denture model data and the model vertex data of each denture to obtain a plurality of model surface patch data corresponding to each denture; and
and calculating to obtain the volume data of the denture model corresponding to each denture according to the data of the plurality of model patches corresponding to each denture by the rear end.
Optionally, the obtaining, by the back end, denture model volume data corresponding to each denture by calculating according to a plurality of model patch data corresponding to each denture includes:
calculating to obtain patch volume data corresponding to each model patch data according to the plurality of model patch data corresponding to each denture through the rear end; and
and respectively combining the surface patch volume data corresponding to each model surface patch data corresponding to each false tooth through the rear end to obtain the denture model volume data corresponding to each false tooth.
Optionally, the denture parameter data comprises the number of teeth included in each denture, the pre-sintered weight, the steps experienced by the denture from the completion of the cut to the pre-sintered denture, and denture selected material data.
Optionally, the calculating, by the back end, the predicted sintered weight of each denture according to the denture model volume data and the corresponding denture parameter data of each denture comprises:
acquiring the volume shrinkage ratio corresponding to each denture through the data of the denture model volume of the posterior end based on each denture;
obtaining, by the back end, an average weight variation ratio corresponding to each denture according to the number of each denture included in each denture, the pre-sintering weight, the steps from the cutting completion to the pre-sintering denture, and the denture selected material data; and
and calculating to obtain the predicted sintered weight corresponding to each denture according to the denture model volume data, the volume shrinkage ratio and the average weight change ratio of each denture by the rear end.
Optionally, said receiving, by said server, said predicted post-sinter weight and said actual post-sinter weight of said each denture, determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sinter weight and said actual post-sinter weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said back end, comprises:
comparing the actual sintered weight of the service end on the basis of each denture with the predicted sintered weight of each denture respectively to obtain at least one difference value corresponding to each denture;
obtaining a minimum difference value from the at least one difference value corresponding to each denture through the server, or respectively sequencing the at least one difference value corresponding to each denture according to the magnitude of the difference values and obtaining M difference values before sequencing, wherein the first difference value is the minimum difference value; and
determining denture order data corresponding to the minimum difference value corresponding to each denture as candidate denture order data through the server, and sending at least one candidate denture order data corresponding to each denture to the back end, or determining the first M difference values corresponding to each denture as at least one candidate denture order data, and sending at least one candidate denture order data corresponding to each denture to the back end.
One aspect of the present invention further provides a denture sorting assisting method, applied to a user side, where the method includes:
receiving denture model data corresponding to at least one denture and denture parameter data input by a user;
calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture;
calculating to obtain the predicted sintered weight of each denture according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to a server;
after each denture is placed into the same sintering furnace for sintering, acquiring the actual sintered weight of each denture, and sending the actual sintered weight of each denture to the server, so that the server: determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sintering weight and said actual post-sintering weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said user end; and
receiving at least one candidate denture order data corresponding to each denture and sent by the server;
and according to the received at least one candidate denture order data corresponding to each denture, determining target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture so as to realize the sorting of each denture.
One aspect of the present invention further provides a denture sorting aid for use at a user end, the denture sorting aid comprising:
the data receiving module is used for receiving denture model data corresponding to at least one denture and denture parameter data input by a user;
the volume calculation module is used for calculating denture model volume data corresponding to each denture according to the denture model data of each denture;
the weight calculation module is used for calculating and obtaining the predicted sintered weight of each denture according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to the server;
a weight obtaining module, configured to obtain, after each denture is placed in the same sintering furnace for sintering, an actual sintered weight of each denture, and send the actual sintered weight of each denture to the server, so that the server: determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sintering weight and said actual post-sintering weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said user end; and
the order receiving module is used for receiving at least one candidate denture order data corresponding to each denture and sent by the server; and
an order determining module, configured to determine, according to the received at least one candidate denture order data corresponding to each denture, target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture, so as to achieve sorting of each denture.
An aspect of an embodiment of the present invention further provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above denture sorting assist method when executing the computer program.
An aspect of an embodiment of the present invention further provides a computer-readable storage medium, including a memory, a processor, and a computer program stored on the memory and executable on at least one processor, the at least one processor implementing the steps of the denture sorting aid method as described above when executing the computer program.
The denture sorting assisting method, the denture sorting assisting device, the computer equipment and the computer readable storage medium provided by the embodiment of the invention receive denture model data and corresponding denture parameter data corresponding to at least one denture sent by the front end through the rear end, wherein the denture model data and the denture parameter data are data obtained by the front end based on the operation of a user in a preset area of the front end; calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture through the rear end; calculating to obtain the predicted sintered weight of each denture through the back end according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to the server; after each denture is placed into the same sintering furnace for sintering, acquiring the actually sintered weight of each denture through the rear end, and sending the actually sintered weight of each denture to the server; receiving, by the server, the predicted post-sinter weight and the actual post-sinter weight of the each denture, determining at least one candidate denture order data corresponding to the each denture based on the predicted post-sinter weight and the actual post-sinter weight of the each denture, and sending the at least one candidate denture order data corresponding to the each denture to the backend; determining, by the back end, target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture according to the received at least one candidate denture order data corresponding to each denture, so as to achieve sorting of each denture; according to the embodiment of the invention, the sintered weight of the false tooth is intelligently predicted through an algorithm, and is quickly compared with the actual sintered weight of the false tooth, so that the false tooth can be quickly sorted by a user, and the sorting efficiency is effectively improved; the false tooth volume data and the false tooth parameter data are combined to predict the weight of the false tooth after sintering and sort the false tooth, so that the sorting accuracy of the false tooth can be improved.
The invention is described in detail below with reference to the drawings and specific examples, but the invention is not limited thereto.
Drawings
Fig. 1 schematically illustrates an example flowchart of a denture sorting assistance method according to a first embodiment of the invention;
fig. 2 schematically illustrates an example flow chart of a denture sorting aid method according to a first embodiment of the invention;
fig. 3 schematically illustrates an example flow chart of a denture sorting aid method according to a first embodiment of the invention;
fig. 4 schematically illustrates an example flow chart of a denture sorting aid method according to a first embodiment of the invention;
fig. 5 schematically illustrates an example flow chart of a denture sorting aid method according to a first embodiment of the invention;
fig. 6 schematically illustrates an example flow chart of a denture sorting aid method according to a first embodiment of the invention;
fig. 7 schematically illustrates an example flow chart of a denture sorting aid method according to a second embodiment of the invention;
fig. 8 schematically shows a block diagram of a denture sorting aid according to a third embodiment of the present invention; and
fig. 9 schematically illustrates a hardware architecture diagram of a computer device suitable for implementing a denture sorting aid method according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the descriptions relating to "first", "second", etc. in the embodiments of the present invention are only for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between the embodiments may be combined with each other, but must be based on the realization of the technical solutions by a person skilled in the art, and when the technical solutions are contradictory to each other or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
In the description of the present invention, it should be understood that the numerical references before the steps do not identify the order of performing the steps, but merely serve to facilitate the description of the present invention and to distinguish each step, and thus should not be construed as limiting the present invention.
Example one
Referring to fig. 1, a flowchart illustrating steps of a denture sorting assisting method according to an embodiment of the present invention is shown. It is to be understood that the flow charts in the embodiments of the present method are not intended to limit the order in which the steps are performed. The false tooth sorting auxiliary method is applied to a false tooth sorting auxiliary system, the false tooth sorting auxiliary system comprises a user side and a server side, the user side comprises a front end and a rear end, false tooth sorting auxiliary software or an application program runs on the rear end, the front end displays an operation interface corresponding to the software or the application program and used for a user to operate, the user side is connected with the server side, the user side and the server side are connected in any mode of wired network connection, wireless network connection, bluetooth connection and the like, and the false tooth sorting auxiliary method is not limited as long as the mode of data transmission between the user side and the server side can be realized. The following description takes the user side and the server side in the denture sorting assisting system as execution subjects, specifically as follows:
as shown in fig. 1, the denture sorting assisting method may include steps S100 to S110, wherein:
step S100, receiving, by the back end, denture model data and denture parameter data corresponding to at least one denture sent by the front end, where the denture model data and the denture parameter data are data obtained by the front end based on an operation of a user in a preset area of the front end.
For example, the denture model data may be data transmitted by a user in a stl format file, may be data transmitted by a user in a cad format file, and may be in a data format that a server can analyze and recognize. The denture parameter data includes, but is not limited to, the number of denture items included in each denture, the weight before sintering, the steps from cutting completion to denture completion before sintering, and denture selected material data, wherein the denture selected material data is denture finished material, and the exact density corresponding to the denture selected material data selected or inputted by the user can be searched in a database running on the preset database. Specifically, the density data corresponding to the finished denture processing material of each manufacturer are public data, are collected and verified in advance, and are stored in a preset database in an associated manner.
And S102, calculating to obtain the corresponding volume data of the artificial tooth model of each artificial tooth through the rear end according to the artificial tooth model data of each artificial tooth.
Firstly, the design model of each denture is a closed body, and accurate denture model volume data corresponding to each denture can be calculated by the back end through an algorithm built in denture sorting auxiliary software.
Referring to fig. 2, the step S102 of obtaining the denture model volume data corresponding to each denture by calculating according to the denture model data of each denture through the back end may further include steps S200 to S204, wherein: step S200, determining model vertex data of each denture through the rear end according to the denture model data of each denture; step S202, segmenting each denture through the rear end according to the denture model data and the model vertex data of each denture to obtain a plurality of model surface patch data corresponding to each denture; and step S204, calculating to obtain the dental prosthesis model volume data corresponding to each artificial tooth through the back end according to the plurality of model surface patch data corresponding to each artificial tooth. In this embodiment, the plurality of model patch data is a plurality of triangle patch data. And the back end cuts each denture according to the denture model data and the model vertex data of each denture to obtain a plurality of triangular patch data corresponding to each denture, and calculates to obtain the denture model volume data corresponding to each denture according to the triangular patch data obtained by cutting.
Referring to fig. 3, the step S204 of obtaining the dental prosthesis model volume data corresponding to each dental prosthesis by calculating according to the plurality of model patch data corresponding to each dental prosthesis by the back end may further includeTo be obtained by the following operations: step S300, calculating to obtain patch volume data corresponding to each model patch data according to a plurality of model patch data corresponding to each denture through the rear end; and step S302, respectively combining the surface patch volume data corresponding to each model surface patch data corresponding to each false tooth through the rear end to obtain the artificial tooth model volume data corresponding to each false tooth. As shown in the above example, the denture sorting auxiliary software at the rear end obtains a first triangular patch by calling a function method of a math library in a Python standard library, and obtains three vertexes of the first triangular patch, wherein three vertexes correspond to three-dimensional coordinates (x) in a counterclockwise sequence 11 ，y 11 ，z 11 ）、（x 12 ，y 12 ，z 12 ）、（x 13 ，y 13 ，z 13 ) Based on the three vertex coordinates of the first triangle patch and equation 1:
V i = |(−x i3 y i2 z i1 +x i2 y i3 z i1 +x i3 y i1 z i2 −x i1 y i3 z i2 −x i2 y i1 z i3 +x i1 y i2 z i3 ) (1/6) |, calculating to obtain patch volume data V1 of the first triangular patch, wherein V i Representing the patch volume data corresponding to the ith model patch data, wherein x, y and z respectively represent coordinate values of three vertexes in the model patch data in a three-dimensional space coordinate system, and by analogy, calculating to obtain patch volume data corresponding to each triangular patch, and substituting patch volume data of all triangular patches corresponding to each denture into formula 2: v total =∑ i V i Summing the patch volume data of all triangular patches corresponding to a denture to obtain denture model volume data V corresponding to the denture total 。
For example, taking a certain data of an artificial tooth model as an example, 27557 model vertices are obtained, 55110 model patches are obtained by segmenting the artificial tooth, and the first triangle patch is obtainedThe coordinate values of the three vertexes are x 11 = -1.680549，y 11 = -49.935905，z 11 = -2.455484，x 12 = -1.729336，y 12 = -50.001141，z 12 = -2.456306，x 13 = -1.731409，y 13 = -49.971203，z 13 = -2.481415; substituting the above formula 1 to calculate the patch volume data of the first triangular patch, and repeating the above steps, substituting all triangular patch data into formula 1 to calculate the patch volume data corresponding to each triangular patch, and summing the patch volume data of all triangular patches to obtain the corresponding denture model volume data, for example, 413.79 cubic millimeters.
And step S104, calculating to obtain the predicted sintered weight of each denture through the back end according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to the server.
In this embodiment, the denture model volume data and the corresponding denture parameter data for each denture are input into a preset denture weight prediction model, and the predicted post-sintering weight of each denture is calculated. In an exemplary embodiment, the denture parameter data includes the number of teeth included per denture, the pre-sintering weight, the steps the denture undergoes from the completion of the cut to the pre-sintering, and denture selected material data. Inputting the denture model volume data and the corresponding denture parameter data of each denture into a preset denture weight prediction model can be understood as inputting the number of each denture, the weight before sintering, the steps from cutting completion to denture experience before sintering, denture selected material data (material brand) and the denture model volume data into the preset denture weight prediction model, and calculating the predicted sintered weight of each denture. Further, the predicted sintered weight of each denture is sent to the server, so that the server can store the weight in a preset database.
For example, referring to fig. 4, the step S104 of calculating the predicted sintered weight of each denture according to the denture model volume data and the corresponding denture parameter data of each denture by the back end may further include steps S400 to S404, where: step S400, acquiring the volume contraction ratio corresponding to each denture according to the denture model volume data of the back end on each denture; step S402, obtaining an average weight change ratio corresponding to each denture by the back end according to the number of each denture, the weight before sintering, the steps from the cutting to the denture before sintering and the selected material data of the denture; and step S404, calculating the predicted sintered weight corresponding to each denture by the back end according to the denture model volume data of each denture, the volume shrinkage ratio and the average weight change ratio. In this embodiment, the predicted sintered weight corresponding to each denture is calculated by combining the volume shrinkage ratio, the average weight change ratio, the industrial experience value, and the denture model volume data of each denture.
In an exemplary embodiment, the method further includes constructing a model to be trained, and training based on the model to be trained to obtain the preset denture weight prediction model; as shown in fig. 6, the details are as follows: step S600, obtaining a plurality of sample data of a plurality of sample dentures which are sintered by a plurality of sintering furnaces, wherein the plurality of sample data comprise the number of dentures, the weight before actual sintering, the steps from cutting to denture sintering, the data of materials selected by the dentures and the weight after actual sintering; step S602, classifying a plurality of sample data of the plurality of sample dentures based on the sintering time of the completed sintering and the sintering furnace in which the sample dentures are located, to obtain sample data of a plurality of groups of sample dentures, wherein the sample dentures of the same group are all sintered in the same sintering furnace at the same sintering time; step S604, respectively inputting the sample data of each group of sample dentures into a model to be trained, and outputting the predicted sintered weight of the sample corresponding to each denture in each group of samples; step S606, comparing the predicted sintered weight of the sample corresponding to each denture in each group of samples with the corresponding actual sintered weight to obtain a corresponding loss value; step S608, based on the corresponding loss value, adjusting the model parameters in the model to be trained to obtain trained model parameters; step S610, obtaining the preset denture weight prediction model based on the trained model parameters. In this embodiment, the denture weight prediction model can be understood as a weight change rule before and after denture sintering under different scenes, and needs to be calculated through a large amount of test data, so that a large amount of sample data of actually delivered dentures needs to be collected for repeated verification and adjustment.
And S106, after each denture is placed into the same sintering furnace to be sintered, acquiring the actually sintered weight of each denture through the rear end, and sending the actually sintered weight of each denture to the server.
In this embodiment, after the denture is sintered, the denture is placed on an electronic scale with an accuracy of 0.1mg, the electronic scale is connected to the user side, the user side automatically obtains the counting change of the electronic scale to obtain the actual sintered weight of the corresponding denture, and the actual sintered weight of each denture is transmitted to the server side.
Step S108 of receiving, by the server, the predicted sintered weight and the actual sintered weight of each denture, determining at least one candidate denture order data corresponding to each denture based on the predicted sintered weight and the actual sintered weight of each denture, and transmitting the at least one candidate denture order data corresponding to each denture to the backend.
Referring to fig. 5, the step S108 of receiving, by the server, the predicted sintered weight and the actual sintered weight of each denture, determining at least one candidate denture order data corresponding to each denture based on the predicted sintered weight and the actual sintered weight of each denture, and transmitting the at least one candidate denture order data corresponding to each denture to the server may further include steps S500 to S504, where: step S500, comparing the actual sintered weight of each denture of the service end with the predicted sintered weight of each denture respectively to obtain at least one difference value corresponding to each denture; step S502, obtaining a minimum difference value from the at least one difference value corresponding to each denture through the server, or sequencing the at least one difference value corresponding to each denture according to the magnitude of the values and obtaining M difference values before sequencing, wherein the first difference value is the minimum difference value; and step S504, determining denture order data corresponding to the minimum difference value corresponding to each denture as candidate denture order data through the server, and sending at least one candidate denture order data corresponding to each denture to the back end, or determining M difference values before sequencing corresponding to each denture as at least one candidate denture order data, and sending at least one candidate denture order data corresponding to each denture to the back end. In this embodiment, the plurality of denture order data corresponding to the smallest difference value among the plurality of difference values corresponding to each denture may be determined as candidate denture order data; or, the plurality of difference values corresponding to each denture can be sorted from small to large, and the denture order data corresponding to the M difference values after sorting are determined as candidate denture order data.
Step S110, determining, by the back end, target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture, according to the received at least one candidate denture order data corresponding to each denture, so as to realize sorting of each denture.
The server side displays at least one candidate denture order data corresponding to each denture on a display interface of the user side, namely the server side directly displays the most similar denture order data of each denture to the user, and then the server side assists the user in completing sorting.
In order to make it easier to understand the denture sorting aid method according to the present invention, denture a is as follows: the repairing type is full crown, the number of the false teeth is 1, the brand of the material is zirconia st, and the steps from the completion of cutting to the false teeth before sintering are only powder blowing, which are described as follows:
the weight average ratio of change before and after sintering of the previous example was calculated to be 0.995469991, the density obtained by manufacturers of certain brand zirconia st was greater than 6.02g/cm, and the corresponding empirical values for the industry were: 6.07g/cm, shrinkage ratio of volume after sintering was 1.25, volume of denture a was 413.79 cubic mm according to the above data, and weight calculation after sintering was predicted to be:
413.79/1000/1.25 by 6.07 by 0.995469991=2.00026180191 grams; combining the following table one:
| serial number | Type of repair | Number of dentures | Material | Weight before sintering (gram) | Sintered weight (gram) | Ratio of change in weight | Steps from cutting to denture processing before sintering |
| 1 | Whole crown | 1 | Certain brand of zirconia st | 3.3478 | 3.3315 | 0.995131131 | Blowing powder |
| 2 | Whole crown | 1 | Certain brand of zirconia st | 1.6587 | 1.6512 | 0.995478387 | Blowing powder |
| 3 | Whole crown | 1 | Certain brand of zirconia st | 1.1716 | 1.1663 | 0.995476272 | Blowing powder |
| 4 | Whole crown | 1 | Certain brand of zirconia st | 1.1945 | 1.1891 | 0.99547928 | Blowing powder |
| 5 | Whole crown | 1 | Certain brand of zirconia st | 1.0392 | 1.0329 | 0.993937644 | Blowing powder |
| 6 | Whole crown | 1 | Certain brand of zirconia st | 0.5396 | 0.5367 | 0.994625649 | Blowing powder |
| 7 | Whole crown | 1 | Certain brand of zirconia st | 1.1512 | 1.1454 | 0.994961779 | Blowing powder |
| 8 | Whole crown | 1 | Certain brand of zirconia st | 1.4187 | 1.4111 | 0.994642983 | Blowing powder |
| 9 | Whole crown | 1 | Certain brand of zirconia st | 1.2127 | 1.2065 | 0.994887441 | Blowing powder |
| 10 | Whole crown | 1 | Certain brand of zirconia st | 0.9427 | 0.9365 | 0.993423146 | Blowing powder |
| 11 | Whole crown | 1 | Certain brand of zirconia st | 1.3061 | 1.3020 | 0.996860884 | Blowing powder |
| 12 | Whole crown | 1 | Certain brand of zirconia st | 3.3341 | 3.325 | 0.997270628 | Blowing powder |
| 13 | Whole crown | 1 | Certain brand of zirconia st | 2.0356 | 2.0277 | 0.99611908 | Blowing powder |
| 14 | Whole crown | 1 | Certain brand of zirconia st | 1.6716 | 1.6681 | 0.997906198 | Blowing powder |
| 15 | Whole crown | 1 | Certain brand of zirconia st | 1.3251 | 1.3196 | 0.99584937 | Blowing powder |
Table one: data relating to dentures in the same sintering furnace
From the above calculation results, the denture closest to denture a was determined to be denture No. 13.
According to the embodiment of the invention, the sintered weight of the false tooth is intelligently predicted through the algorithm, and is rapidly compared with the actual sintered weight of the false tooth, so that a user can be assisted to rapidly sort the false tooth, and the sorting efficiency is effectively improved; the false tooth volume data and the false tooth parameter data are combined to predict the sintered weight of the false tooth and sort the false tooth, so that the false tooth sorting accuracy can be improved.
The denture sorting auxiliary scheme in the embodiment of the invention also has at least the following beneficial effects:
(1) The false tooth sorting method can quickly realize false tooth sorting. In the whole process, a user can quickly and accurately sort by only uploading denture model data once and selecting denture parameter data of finished product materials of each denture, so that the sorting efficiency can be greatly improved, the error probability is reduced, a printing die is not needed any more, and the professional requirements of a technician are not required any more; it is a qualitative leap for denture factories.
(2) The weight of the false teeth after sintering can be accurately predicted through the false tooth weight prediction model and the false tooth model volume algorithm, the sorting efficiency is effectively improved, and a user is assisted in realizing the rapid sorting of the false teeth.
Example two
Referring to fig. 7, a flowchart of steps of a method for assisting tooth sorting according to an embodiment of the invention is shown. It is to be understood that the flow charts in the embodiments of the present method are not intended to limit the order in which the steps are performed. The false tooth sorting auxiliary method is applied to a user side. The following exemplary descriptions are respectively given by taking the user side as an execution subject, and specifically include the following steps:
as shown in fig. 7, the denture sorting assisting method may include steps S700 to S710, wherein:
step S700, receiving denture model data corresponding to at least one denture and denture parameter data input by a user;
step S702, calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture;
step S704, calculating to obtain the predicted sintered weight of each denture according to the denture model volume data of each denture and corresponding denture parameter data, and sending the predicted sintered weight of each denture to a server;
step S706, after each denture is placed in the same sintering furnace for sintering, obtaining the actual sintered weight of each denture, and sending the actual sintered weight of each denture to the server, so that the server: determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sintering weight and said actual post-sintering weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said user end; and
step S708, receiving at least one candidate denture order data corresponding to each denture sent by the server; and
step S710, determining target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture according to the received at least one candidate denture order data corresponding to each denture, so as to realize sorting of each denture.
EXAMPLE III
With reference to fig. 8, a schematic block diagram of a denture sorting assist apparatus 80 according to an embodiment of the present invention is shown. In this embodiment, the denture sorting aid 80 may include or be divided into one or more program modules, which are stored in an embedded memory chip and executed by one or more processors, to implement the present invention and implement the denture sorting aid method described above. The program modules referred to in the embodiments of the present invention refer to a series of computer program instruction segments capable of performing specific functions, and are better suited than the program itself for describing the execution process of the denture sorting aid 80 in a storage medium. The following description will specifically describe the functions of the program modules of the present embodiment:
the device comprises: a data receiving module 800, a volume calculating module 802, a weight calculating module 804, a weight obtaining module 806, an order receiving module 808, and an order determining module 810, wherein:
a data receiving module 800, configured to receive denture model data corresponding to at least one denture and denture parameter data input by a user;
the volume calculation module 802 is configured to calculate, according to the denture model data of each denture, denture model volume data corresponding to each denture;
the weight calculation module 804 is configured to calculate a predicted sintered weight of each denture according to the denture model volume data of each denture and corresponding denture parameter data, and send the predicted sintered weight of each denture to the server;
a weight obtaining module 806, configured to obtain an actual sintered weight of each denture after each denture is placed in the same sintering furnace for sintering, and send the actual sintered weight of each denture to the server, so that the server: determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sintering weight and said actual post-sintering weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said user end; and
an order receiving module 808, configured to receive at least one candidate denture order data corresponding to each denture sent by the server; and
an order determining module 810, configured to determine, according to the received at least one candidate denture order data corresponding to each denture, a target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture, so as to realize sorting of each denture.
Example four
Fig. 9 schematically shows a hardware architecture diagram of a computer apparatus 10000 suitable for implementing a denture sorting aid method according to a fourth embodiment of the present invention. In this embodiment, the computer device 10000 is a device capable of automatically performing score calculation and/or information processing according to a preset or stored instruction. For example, the server may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a cabinet server (including an independent server or a server cluster composed of multiple servers), a gateway, and the like. As shown in fig. 9, computer device 10000 includes at least, but is not limited to: the memory 10010, the processor 10020, and the network interface 10030 may be communicatively linked to each other through a system bus. Wherein:
the memory 10010 includes at least one type of computer-readable storage medium comprising flash memory, hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disks, optical disks, etc. In some embodiments, the storage 10010 can be an internal storage module of the computer device 10000, such as a hard disk or a memory of the computer device 10000. In other embodiments, the memory 10010 can also be an external storage device of the computer device 10000, such as a plug-in hard disk provided on the computer device 10000, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Of course, the memory 10010 may also comprise both an internal memory module of the computer device 10000 and an external memory device thereof. In this embodiment, the memory 10010 is generally configured to store an operating system installed on the computer device 10000 and various types of application software, such as program codes of the denture sorting aid method. In addition, the memory 10010 can also be used to temporarily store various types of data that have been output or are to be output.
Processor 10020 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data Processing chip in some embodiments. The processor 10020 is generally configured to control overall operations of the computer device 10000, such as performing control and processing related to data interaction or communication with the computer device 10000. In this embodiment, the processor 10020 is configured to execute the program code stored in the memory 10010 or process data.
Network interface 10030 may comprise a wireless network interface or a wired network interface, and network interface 10030 is generally used to establish a communication link between computer device 10000 and other computer devices. For example, the network interface 10030 is used to connect the computer device 10000 to an external terminal through a network, establish a data transmission channel and a communication link between the computer device 10000 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a Global System of Mobile communication (GSM), wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, bluetooth (Bluetooth), or Wi-Fi.
It should be noted that fig. 9 only illustrates a computer device having components 10010-10030, but it should be understood that not all of the illustrated components are required to be implemented, and that more or fewer components may be implemented instead.
In this embodiment, the denture sorting aid method stored in the memory 10010 can be further divided into one or more program modules and executed by a processor (the processor 10020 in this embodiment) to complete the embodiment of the present invention.
EXAMPLE five
The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by at least one processor, implements the steps of the denture sorting aid method in embodiments.
In this embodiment, the computer-readable storage medium includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the computer readable storage medium may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the computer-readable storage medium may be an external storage device of the computer device, such as a plug-in hard disk provided on the computer device, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Of course, the computer-readable storage medium may also include both internal and external storage devices of the computer device. In this embodiment, the computer-readable storage medium is generally used for storing an operating system and various types of application software installed on a computer device, for example, the program code of the denture sorting assistance method in the embodiment, and the like. In addition, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are to be output.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A denture sorting aid method, for use in a denture sorting aid system, the denture sorting aid system comprising a user side and a server side, the user side comprising a front end and a back end, the method comprising:
receiving, by the back end, denture model data and denture parameter data corresponding to at least one denture sent by the front end, wherein the denture model data and the denture parameter data are data obtained by the front end based on a user's operation on a preset area of the front end;
calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture through the rear end;
calculating to obtain the predicted sintered weight of each denture according to the denture model volume data and the corresponding denture parameter data of each denture by the back end, and sending the predicted sintered weight of each denture to the server;
after each denture is placed into the same sintering furnace for sintering, acquiring the actual sintered weight of each denture through the rear end, and sending the actual sintered weight of each denture to the server;
receiving, by the server, the predicted post-sinter weight and the actual post-sinter weight of the each denture, determining at least one candidate denture order data corresponding to the each denture based on the predicted post-sinter weight and the actual post-sinter weight of the each denture, and sending the at least one candidate denture order data corresponding to the each denture to the backend; and
determining, by the back end, a target denture order data for each denture from the at least one candidate denture order data for each denture to enable a sorting of the each denture, based on the received at least one candidate denture order data for the each denture.
2. The denture sorting assisting method according to claim 1, wherein the calculating, by the back end, denture model volume data corresponding to each denture from denture model data of each denture comprises:
determining model vertex data for each denture from the denture model data for each denture by the back end;
segmenting each denture through the rear end according to the denture model data and the model vertex data of each denture to obtain a plurality of model surface patch data corresponding to each denture; and
and calculating to obtain the data of the artificial tooth model volume corresponding to each artificial tooth through the back end according to the data of the plurality of model patches corresponding to each artificial tooth.
3. The denture sorting assisting method according to claim 2, wherein the calculating, by the back end, denture model volume data corresponding to each denture from the plurality of model patch data corresponding to each denture comprises:
calculating to obtain patch volume data corresponding to each model patch data according to the plurality of model patch data corresponding to each denture through the rear end; and
and respectively combining the surface patch volume data corresponding to each model surface patch data corresponding to each false tooth through the rear end to obtain the artificial tooth model volume data corresponding to each false tooth.
4. The denture sorting aid according to claim 2, wherein the denture parameter data comprises a number included in each denture, a pre-sintering weight, steps experienced by the denture from completion of cutting to pre-sintering, and denture selected material data.
5. The denture sorting aid of claim 4, wherein said calculating a predicted post-sintering weight for each denture by said back end from said denture model volume data for said each denture and corresponding denture parameter data comprises:
acquiring the volume shrinkage ratio corresponding to each denture through the data of the denture model volume of the posterior end based on each denture;
obtaining, by the back end, an average weight variation ratio corresponding to each denture according to the number of each denture included in each denture, the pre-sintering weight, the steps from the cutting completion to the pre-sintering denture, and the denture selected material data; and
and calculating to obtain the predicted sintered weight corresponding to each denture according to the denture model volume data, the volume shrinkage ratio and the average weight change ratio of each denture by the rear end.
6. The denture sorting aid method according to claim 1, wherein said receiving, by said server, said predicted post-sinter weight and said actual post-sinter weight of said each denture, determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sinter weight and said actual post-sinter weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said back end comprises:
comparing the actual sintered weight of the service end on the basis of each denture with the predicted sintered weight of each denture respectively to obtain at least one difference value corresponding to each denture;
obtaining a minimum difference value from the at least one difference value corresponding to each denture through the server, or respectively sequencing the at least one difference value corresponding to each denture according to the magnitude of the difference values and obtaining M difference values before sequencing, wherein the first difference value is the minimum difference value; and
determining denture order data corresponding to the minimum difference value corresponding to each denture as candidate denture order data through the server, and sending at least one candidate denture order data corresponding to each denture to the back end, or determining the first M difference values corresponding to each denture as at least one candidate denture order data, and sending at least one candidate denture order data corresponding to each denture to the back end.
7. A denture sorting assisting method applied to a user side, the method comprising:
receiving denture model data corresponding to at least one denture and corresponding denture parameter data input by a user;
calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture;
calculating to obtain the predicted sintered weight of each denture according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to a server;
after each denture is placed into the same sintering furnace for sintering, the actual sintered weight of each denture is obtained, and the actual sintered weight of each denture is sent to the server, so that the server: determining at least one candidate denture order data corresponding to said each denture based on said predicted post-sintering weight and said actual post-sintering weight of said each denture, and sending said at least one candidate denture order data corresponding to said each denture to said user end; and
receiving at least one candidate denture order data corresponding to each denture and sent by the server;
and according to the received at least one candidate denture order data corresponding to each denture, determining target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture so as to realize the sorting of each denture.
8. A denture sorting aid, for use at a user end, the aid comprising:
the data receiving module is used for receiving denture model data corresponding to at least one denture and denture parameter data input by a user;
the volume calculation module is used for calculating to obtain denture model volume data corresponding to each denture according to the denture model data of each denture;
the weight calculation module is used for calculating and obtaining the predicted sintered weight of each denture according to the denture model volume data of each denture and the corresponding denture parameter data, and sending the predicted sintered weight of each denture to the server;
a weight obtaining module, configured to obtain an actual sintered weight of each denture after each denture is placed in the same sintering furnace for sintering, and send the actual sintered weight of each denture to the server, so that the server: determining at least one candidate denture order data corresponding to each denture based on the predicted sintered weight and the actual sintered weight of each denture, and sending the at least one candidate denture order data corresponding to each denture to the user-side; and
the order receiving module is used for receiving at least one candidate denture order data corresponding to each denture and sent by the server; and
an order determining module, configured to determine, according to the received at least one candidate denture order data corresponding to each denture, target denture order data corresponding to each denture from the at least one candidate denture order data corresponding to each denture, so as to achieve sorting of each denture.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor when executing the computer program is configured to carry out the steps of the denture sorting aid method according to any one of claims 1 to 6.
10. A computer-readable storage medium having stored thereon a computer program which is executable by at least one processor to cause the at least one processor to perform the steps of the denture sorting aid method according to any one of claims 1 to 6.
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Also Published As
| Publication number | Publication date |
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| WO2024045302A1 (en) | 2024-03-07 |
| CN115156087B (en) | 2022-12-13 |
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