Neural Network Tooth Arrangement Generation

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Solution Overview

Problem

The existing methods for generating a target tooth arrangement for orthodontic treatment are laborious, time-consuming, and highly dependent on operator skill, as they involve manual manipulation of 3D digital models, leading to inconsistent results.

Innovation Solution

A computer-implemented method using trained deep artificial neural networks to generate a digital data set representing a target tooth arrangement, where sampling points from a 3D digital model are used to create geometric codes for each tooth, combined to form an overall jaw code, and then processed by a second neural network to produce a target tooth arrangement data set.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual manipulation of 3D digital models is used to generate target tooth arrangement, then flexibility and customization are improved, but labor time and operator dependency increase significantly

Engineering Contradiction:

Improvecustomization flexibilityVSAvoidlabor time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical manipulation of 3D digital models with an automated computer-implemented method. The system uses digital sampling points, geometric coding, and neural network processing to automatically generate target tooth arrangements, eliminating the need for operators to manually manipulate digital models while preserving customization capabilities through programmable parameters.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the computer system to autonomously process the generation of target tooth arrangements without requiring continuous human intervention. Once initial parameters are set, the automated workflow independently completes sampling, geometric coding, and arrangement generation, reducing operator time investment while maintaining adaptability.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If manual manipulation of 3D digital models is used to generate target tooth arrangement, then operator judgment and experience can be applied, but result consistency deteriorates due to skill dependency

Engineering Contradiction:

Improveoperator judgmentVSAvoidresult consistency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent substitutes manual operator judgment with automated decision-making algorithms. The computer-implemented method uses standardized geometric coding and neural network processing to objectively determine target tooth arrangements, eliminating variability introduced by different operator skills while maintaining clinical appropriateness through programmable guidelines.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system transforms subjective operator judgment into objective parameter-based decision making. By converting clinical considerations into quantifiable parameters that guide the automated processing, the system achieves consistent results across different cases and operators while preserving the essence of professional judgment through configurable parameters.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If complex manual manipulation processes are used, then treatment precision can be achieved, but process complexity and time consumption increase

Engineering Contradiction:

Improvetreatment precisionVSAvoidprocess complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex task of generating target tooth arrangements into distinct automated processing stages: sampling point generation, geometric code creation, and neural network-based arrangement optimization. This segmentation simplifies the overall process by breaking it into manageable computational steps that can be executed automatically while maintaining precision.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system replaces complex manual manipulation procedures with automated computational processes. The computer-implemented method uses algorithms and neural networks to perform tasks that would otherwise require lengthy manual operations, reducing process complexity while maintaining or improving treatment precision through systematic digital processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12094055B2Method for generating digital data set representing target tooth arrangement for orthodontic treatment

Publication Date: 2024.09.17 HANGZHOU ZOHO INFORMATION TECH CO LTD

AI summary

One aspect of the present application provides a method for generating a digital data set representing a target tooth arrangement for an orthodontic treatment, the method comprises: obtaining a first 3D digital model representing a jaw under an initial tooth arrangement; sampling on each tooth in the first 3D digital model to obtain a corresponding set of sampling points; generating a corresponding geometric code using a trained first deep artificial neural network, based on each of the sets of sampling points; combining the geometric codes of all teeth to obtain an overall geometric code of the jaw; and generating a digital data set representing the target tooth arrangement for the orthodontic treatment of the jaw using a trained second deep artificial neural network based on the overall geometric code of the jaw.