Dentition Mesh Segmentation for Accurate Oral Structure Mapping
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Solution Overview
Problem
Conventional biomedical imaging systems fail to process complex biomedical data with sufficient speed and granularity to support individualized patient care, particularly in transforming dentition structures.
Innovation Solution
A method and system for transforming a dentition structure by generating a surface geometrically connecting landmarks, identifying boundaries, selecting regions, projecting onto a predetermined plane, and smoothing the model to accurately represent the dentition structure, using a topography engine, image processing engine, and landmark processing engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional biomedical imaging systems are used to process complex biomedical data, then the processing speed and granularity are insufficient to support individualized patient care
Solution Approach 1:
The system segments the complex biomedical imaging process into distinct functional modules: an image processing engine that handles image acquisition and preprocessing, a topography engine that generates 3D surface models from 2D images, and a construction engine that creates anatomical models. This segmentation allows each module to process data independently and efficiently, improving overall processing speed while maintaining manageable system complexity through modular architecture.
2Measurement precision
If conventional biomedical imaging systems are used to process complex biomedical data, then the processing granularity is insufficient to support individualized patient care
Solution Approach 1:
The topography engine performs dimensionality transformation by converting 2D dental images into 3D surface models with precise spatial coordinates. This dimensional upgrade enables individualized patient care by providing detailed granular information about tooth morphology, position, and relationships. The 3D models capture fine anatomical details that are lost in conventional 2D imaging, achieving high measurement precision through the added spatial dimension.
3Manufacturing precision
If a dentition model is reconstructed from multiple images, then distortion may occur in the projected shapes of physical features
Solution Approach 1:
The construction engine uses feedback mechanisms to iteratively refine the dentition model by comparing projected 2D images against the 3D surface model and adjusting parameters to minimize distortion. The system continuously evaluates the alignment between projected features and actual anatomical structures, making corrections to achieve accurate representation of tooth shapes and positions, thereby improving model accuracy through iterative optimization.
Data Source
AI summary
Example implementations include a method of constructing a dentition structure by a topographic mesh therefor, by generating one or more edges geometrically connecting one or more landmarks, the landmarks being associated with one or more physical features of a physical object, generating a mesh model including the edges and the landmarks, identifying at least one boundary of the mesh model based on one or more of the edges and the landmarks, selecting at least one mesh region associated with at least one corresponding physical feature of the physical object, projecting the selected mesh region onto a predetermined projection plane to form a mesh projection, and constructing the physical features of the physical object based on the mesh projection.