Granted Patent B2

US 12,210,802 · App. 17/245,944 · Granted Jan 28, 2025

Inventors: Sergei Azernikov (Irvine, CA); Simon Karpenko (Newport Beach, CA)

Assignee: James R. Glidewell Dental Ceramics, Inc.

G06F30/10G06F30/23G06F30/27G06N3/045G06N3/08G06T17/20G06T2210/41

Abstract

Claims (31)

1. A computer-implemented method of automatic margin line proposal, comprising:

receiving a 3D digital model of at least a portion of a jaw, the 3D digital model comprising a digital preparation tooth;

determining, using a first trained neural network, an inner representation of the 3D digital model; and

determining, using a second trained neural network, a margin line proposal from a base margin line and the inner representation of the 3D digital model,

wherein the first trained neural network and the second trained neural network are trained using a training dataset comprising an untrimmed digital surface of the jaw and a target margin line on a surface of the corresponding trimmed digital surface.

2. The method of claim 1 , wherein the base margin line comprises one or more digital points defining the margin of the digital preparation tooth.

3. The method of claim 1 , wherein the 3D digital model comprises a 3D point cloud.

4. The method of claim 1 , wherein the first trained neural network comprises a trained hierarchal neural network (“HNN”).

5. The method of claim 1 , wherein the first trained neural network comprises a neural network for 3D point cloud analysis.

6. The method of claim 1 , wherein the second trained neural network comprises a decoder neural network.

7. A system for automatic margin line proposal, comprising:

a processor; and

a computer-readable storage medium comprising instructions executable by the processor to perform steps comprising:

receiving a 3D digital model of at least a portion of a jaw, the 3D digital model comprising a digital preparation tooth;

determining, using a first trained neural network, an inner representation of the 3D digital model; and

determining, using a second trained neural network, a margin line proposal from a base margin line and the inner representation of the 3D digital model,

wherein the first trained neural network and the second trained neural network are trained using a training dataset comprising an untrimmed digital surface of the jaw and a target margin line on a surface of the corresponding trimmed digital surface.

8. The system of claim 7 , wherein the second trained neural network comprises a decoder neural network.

9. The system of claim 7 , wherein the base margin line comprises one or more digital points defining the margin of the digital preparation tooth.

10. The system of claim 7 , wherein the 3D digital model is a 3D point cloud.

11. The system of claim 7 , wherein the first trained neural network comprises a trained hierarchal neural network (“HNN”).

12. The system of claim 7 , wherein the first trained neural network comprises a neural network for 3D point cloud analysis.

13. A non-transitory computer readable medium storing executable computer program instructions to automatically propose a margin line, the computer program instructions comprising:

receiving a 3D digital model of at least a portion of a jaw, the 3D digital model comprising a digital preparation tooth;

determining, using a first trained neural network, an inner representation of the 3D digital model; and

determining, using a second trained neural network, a margin line proposal from a base margin line and the inner representation of the 3D digital model,

wherein the first trained neural network and the second trained neural network are trained using a training dataset comprising an untrimmed digital surface of the jaw and a target margin line on a surface of the corresponding trimmed digital surface.

14. The medium of claim 13 , wherein the first trained neural network comprises a trained hierarchal neural network (“HNN”).

15. The medium of claim 13 , wherein the second trained neural network comprises a decoder neural network.

16. The medium of claim 13 , wherein the base margin line comprises one or more digital points defining the margin of the digital preparation tooth.

17. The medium of claim 13 , wherein the 3D digital model is a 3D point cloud.

Assignments (1)

Continuity (1)

References Cited (249)