4D Virtual Head and Teeth Model Generation
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Solution Overview
Problem
Current methods for creating virtual patient models in dentistry are limited by the need for multiple static facial scans, which result in imprecise alignment, unnatural facial expressions, and a time-consuming process that does not accurately capture facial dynamics.
Innovation Solution
A method that generates a four-dimensional virtual model of a patient's head and denture by performing a single neutral-position facial scan and recording a video of the patient's facial movements, which are then transferred to the 3D mesh to create a dynamic and realistic virtual patient model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple static facial scans are performed to capture different facial positions, then facial references can be obtained, but the process becomes time-consuming and results in misalignment between meshes
Solution Approach 1:
The patent applies dynamics by transitioning from static facial scans to dynamic video capture. The system records videos of the patient performing various facial expressions (smiling, talking, resting) and uses image processing algorithms to extract 3D facial models from these dynamic sequences. This allows capture of facial dynamics and multiple positions in a single recording session, eliminating the need for multiple separate static scans and reducing misalignment issues.
Solution Approach 2:
The patent introduces the time dimension to facial scanning by using video recordings instead of static images. By capturing facial movements across time and extracting 3D models from video sequences, the system obtains comprehensive facial references including dynamic characteristics. This dimensional addition allows simultaneous capture of multiple facial positions and expressions without requiring multiple separate scanning sessions.
2Measurement precision
If multiple static facial scans are performed to capture different facial positions, then facial references can be obtained, but the alignment between meshes becomes imprecise
Solution Approach 1:
The patent implements feedback mechanisms through automated alignment algorithms that process video frames sequentially. The system extracts 3D models from video sequences and automatically aligns them using feature recognition and registration algorithms. This feedback loop continuously adjusts and refines mesh alignment based on detected facial landmarks and geometric consistency, ensuring precise alignment without manual intervention.
Solution Approach 2:
The patent creates digital copies of the patient's face from video sequences by extracting 3D models from multiple video frames. These digital copies are then automatically aligned and integrated into a unified 3D facial model. The copying process preserves facial geometry and dynamics while enabling precise alignment through computational algorithms, eliminating the alignment errors that occur when manually integrating multiple static scans.
3Device complexity
If static 3D models are used to represent the patient, then the model is simple, but it cannot simulate facial dynamics and movements
Solution Approach 1:
The patent transforms the static 3D model into a dynamic virtual patient by incorporating facial movement data extracted from videos. The system records patients performing various expressions and mouth movements, then integrates this dynamic information into the 3D model. This allows the virtual patient to simulate real facial dynamics, lip movements, and expressions, providing versatility for treatment planning while maintaining manageable complexity through automated processing.
4Productivity
If a single neutral-position facial scan is performed, then the scanning process is simplified and faster, but facial dynamics and movements cannot be captured
Solution Approach 1:
The patent resolves this contradiction by using dynamic video recording that captures facial movements across time. Instead of requiring multiple static scans, the system records videos of patients performing various expressions and mouth movements. Image processing algorithms then extract comprehensive facial dynamics information from these videos, including lip movements, facial expressions, and mouth opening/closing actions, thereby capturing all necessary information in a single efficient recording session.
Solution Approach 2:
The patent applies continuity by using continuous video recording to capture facial dynamics. Rather than discrete static scans, the system records continuous video sequences that capture facial movements in real-time. This continuous capture ensures that all facial dynamics information is obtained in a single uninterrupted session, maximizing productivity while preserving complete dynamic data for accurate virtual patient modeling.
Data Source
AI summary
It refers to the digitalization in three dimensions of a patient's head, intraoral maxillary and mandibular regions and bones. It includes integration of the facial movement to simulate the aesthetical and functional result before medical treatment, which could include surgery, and orthodontic and/or prosthodontic treatments. It comprises: creation of a 3D virtual model of the patient's head (2), creation of a 3D model of the patient's denture (4), fusion and anchoring of the 3D denture model (4) into the 3D head model (2), animation of the 3D head model (2) from 2D images (5) of the patient, resulting in an animated 3D model (6), animation of the 3D denture model (4) from 2D images (5) of the patient, and fusion with the 3D animated model (6), obtaining an animated 3D model of the patient's head and denture (7).