METHOD FOR DESIGNING A DENTAL COMPONENT

Abstract

A method for designing a dental component, specifically a restoration, a bite guard or an impression tray, comprising the steps of measuring a dental situation; generating a 3D model of the dental situation; applying an artificial neural network for machine learning (convolutional neural network; CNN) to the 3D model of the dental situation and/or an initial 3D model of the dental component, and automatically generating a fully designed 3D model of the dental component, specifically the restoration, the bite guard or the impression tray.

Claims

1. A method for designing a dental component, comprising the steps of: measuring a dental situation; generating a 3D model of the dental situation; applying an artificial neural network for machine learning (convolutional neural network; CNN) to the 3D model of the dental situation and/or an initial 3D model of the dental component, and automatically generating a fully designed 3D model of the dental component.

2. The method according to claim 1, wherein the neural network is trained on the basis of a training data set, wherein the training data set includes initial 3D models of initial dental components and manual changes of these initial 3D models during the design of the 3D model of at least one user.

3. The method according to claim 1, wherein the neural network is trained on the basis of a training data set, wherein the training data set includes a plurality of 3D models of a plurality of dental situations and the corresponding 3D models of fully designed initial dental components of at least one user.

4. The method according to claim 2, wherein the training data set only contains the data of one user or of a group of experienced users.

5. The method according to claim 2, wherein the neural network remains unchanged after training on the basis of the training data set.

6. The method according to claim 2, wherein new data are added to the training data set so that the neural network is trained further on the basis of the expanded training data set.

7. The method according to claim 1, wherein the dental component is the restoration, wherein the restoration is an inlay, a crown, a crown framework, a bridge, a bridge framework, an abutment, a pontic or a veneer.

8. The method according to claim 7, wherein the 3D model of the dental situation has at least one tooth for inserting the dental component, at least one preparation, one residual tooth, at least one neighboring tooth, an abutment for inserting the dental component to be produced, color information of the dental situation and/or a color gradient of the dental situation.

9. The method according to claim 8, wherein the neural network uses color information and/or a color gradient of the 3D model of the dental situation, specifically the residual tooth and/or at least one neighboring tooth, to automatically specify a color and/or a color gradient for the restoration to be inserted.

10. The method according to claim 7, wherein the neural network automatically specifies a material, a production method, an insertion method, a tapping position and/or a contact tightness with respect to the neighboring teeth for the dental component to be produced.

11. The method according to claim 7, wherein the training data set additionally includes a color, a color gradient, a material, a production method, an insertion method, a tapping position and/or a contact tightness with respect to the neighboring teeth of the fully designed dental component.

12. The method according to claim 1, wherein the dental component is a bite guard or an impression tray, wherein the 3D model of the dental situation comprises the teeth for placing the bite guard or the impression tray.

13. The method according to claim 12, wherein the neural network automatically specifies a material and/or a production method for the bite guard or the impression tray to be produced.

14. A device for data processing, comprising means for carrying out the method according to any one of claims 1-13.

15. A computer program, comprising commands which, when the computer program is executed by a computer, cause the computer to carry out the method according to claim 1.

16. A computer-readable storage medium comprising commands which, when executed by a computer, cause the computer to carry out the method according to claim 1.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The invention is explained with reference to the drawings. The following is shown:

[0075] FIG. 1 shows a drawing to illustrate the method for designing a component;

[0076] FIG. 2 shows a drawing of an initial 3D model.

EXEMPLARY EMBODIMENTS

[0077] FIG. 1 shows a drawing to illustrate the method for designing a component 1, such as an implant-supported kill crown 2, a full crown 4 supported by a preparation 3 or an implant supported bridge 5. The component 1 can also be a bite guard or an impression tray. A dental camera 6 is used to measure a dental situation 7, including teeth 8 and gums 9, and a 3D model 10 of the dental situation 7 is calculated from the image data, which 3D model can be displayed by means of a display device 11 such as a monitor. The display device 11 is connected to a computer 12, with an input device such, as a keyboard 13 or a mouse 14 being connected to the computer 12 and enabling the user to navigate by means of a cursor 15 within a graphic representation of the 3D model 10. The dental situation 7 has a missing canine tooth, an incisor with a preparation 3 and three missing molars of the lower jaw. An implant-supported full crown 2 should replace the canine tooth, the full crown 4 should be placed on the preparation 3, and the bridge 5 to be designed should replace the three missing molars, as indicated by arrows 16, 17 and 18. In a first step, the user can manually use the cursor 15 to specify a first position of a first component to be designed and inserted, specifically an implant-supported crown 2, and select the type of component, specifically an implant-supported crown, in a selection menu 20. In a second step, a 3D model 21 of the component, specifically the implant-supported full crown 2, is automatically generated by means of a neural CNN network which has been trained on the basis of a training data set for the relevant user and the relevant type of component. Accordingly, the position 22 of the full crown 4 is specified manually and the type of component 1, specifically a full crown supported by a preparation, is selected in the selection menu 20. A second 3D model 23 of the full crown 4 is then generated by means of the corresponding CNN network. The position 24 of the bridge 5 to be inserted is then specified, and the type of component 1 is selected from the selection menu 20. In a further step, a 3D model 25 of the bridge 5 is automatically generated by means of a CNN network for implant-supported bridges and the relevant user. The designed components 2, 4 and 5 can then be produced, for example, automatically from blanks by means of a CAM production device, not shown, using the designed 3D models 21, 23 and 25.

[0078] FIG. 2 shows a drawing of an initial 3D model 30 of the bridge 5 from FIG. 1, wherein the user manually adapts the initial 3D model 30 using CAD tools in order to generate the adjusted 3D model 25 shown in dashed lines, a tapping position 31 is shifted to a tapping position 32 shown in dashed lines, as indicated by the arrow 33, and a contact tightness 34 and 35 of the initial 3D model 30 is reduced to a contact tightness 36 and 37 of the adapted 3D model 25. A large number of such manual changes or adjustments to an initial 3D model 30 for the relevant user and for the relevant type of components, specifically implant-supported bridges, can then be combined in a training data set in order to train an associated CNN network. This trained CNN network, which runs as a program on the computer 12, can then be used to automatically implement the changes or adjustments on the basis of an initial 3D model 30.

REFERENCE SYMBOLS

[0079] 1 Component [0080] 2 Implant-supported full crown [0081] 3 Preparation [0082] 4 Full crown [0083] 5 Implant-supported bridge [0084] 6 Camera [0085] 7 Dental situation [0086] 8 Teeth [0087] 9 Gum [0088] 10 3D model [0089] 11 Display device [0090] 12 Computer [0091] 13 Keyboard [0092] 14 Mouse [0093] 15 Cursor [0094] 16 Arrow [0095] 17 Arrow [0096] 18 Arrow [0097] 19 Position of the implant-supported full crown [0098] 20 Selection menu [0099] 21 3D model the implant-supported full crown [0100] 22 Position of the full crown [0101] 23 3D model of the full crown [0102] 24 Position of the bridge [0103] 25 3D model of the bridge [0104] 26 Implant [0105] 30 Initial 3D model [0106] 31 Tapping position [0107] 32 Tapping position [0108] 33 Arrow [0109] 34 Contact tightness [0110] 35 Contact tightness [0111] 36 Contact tightness [0112] 37 Contact tightness