3D Skull Model Prediction for Dental Treatment Planning
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Solution Overview
Problem
Current methods in dentistry fail to provide accurate predictions or models of aesthetic outcomes for dental treatment plans, lacking effective feedback mechanisms.
Innovation Solution
A method is presented that estimates a three-dimensional (3D) skull model of a patient's facial bone structure using a combination of facial scans, machine learning models, and volumetric mesh generation, allowing for improved visualization and treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional dental treatment planning methods are used, then treatment procedures can be performed, but accurate prediction or modeling of aesthetic outcomes is not provided
Solution Approach 1:
The patent implements feedback by using trained machine learning models to predict aesthetic outcomes of dental treatment plans. The system processes patient-specific 3D skin models and treatment modifications to generate predicted outcome visualizations, providing clinicians and patients with feedback on expected aesthetic results before treatment execution
Solution Approach 2:
The patent creates accurate digital copies of patient facial structures through 3D skin models generated from facial scans. These digital models serve as virtual replicas that can be modified and visualized to predict treatment outcomes without physically altering the patient, enabling accurate outcome prediction through virtual simulation
2Ease of operation
If 3D skull modeling using machine learning is implemented, then non-invasive prediction of skull structure is enabled, but computational complexity and processing requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-training machine learning models on extensive datasets of facial scans and corresponding skull structures before actual use. This pre-training phase creates ready-to-use predictive models that can then rapidly generate skull structure predictions without requiring complex real-time computations during patient consultations
Solution Approach 2:
The patent introduces 3D skin models as intermediary representations between facial scans and skull structure predictions. The trained machine learning models learn to map from skin surface geometry to underlying skull structure, using the skin model as an intermediate step that simplifies the overall prediction process and improves accuracy
Data Source
AI summary
Methods and systems are described for 3D modeling and visualization of a patient's facial structure and features for dental treatment planning.