3D Tooth Image Reconstruction for Accurate Number Detection
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Solution Overview
Problem
Conventional two-dimensional CBCT images face challenges in accurately confirming tooth numbers due to metal artifacts from crowns, leading to inefficiencies in data processing and loading times during dental implant procedures.
Innovation Solution
A three-dimensional tooth image display apparatus and method utilizing an artificial neural network to divide dental cross-sectional images, detect tooth boundaries and numbers, and generate accurate three-dimensional tooth images, reducing data processing throughput and loading times through trained neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional two-dimensional CBCT images are used to confirm tooth numbers, then the imaging process is simple and fast, but metal artifacts from crowns distort the images and make accurate tooth number confirmation difficult
Solution Approach 1:
The patent transitions from two-dimensional CBCT images to three-dimensional tooth images generated by stacking processed cross-sectional images. This dimensional change allows the system to overcome metal artifact interference in 2D views by reconstructing teeth from multiple angular perspectives, enabling accurate tooth number identification through 3D spatial relationships.
Solution Approach 2:
The patent replaces manual visual inspection of 2D CBCT images by dental practitioners with an automated neural network-based 3D tooth image generation and tooth number detection system. The neural networks automatically process cross-sectional images, generate 3D tooth models, and identify tooth numbers, eliminating the need for manual interpretation of artifact-distorted 2D images.
2Measurement precision
If three-dimensional tooth images are generated using neural networks to eliminate metal artifacts, then tooth number detection accuracy improves, but data processing throughput and loading time increase
Solution Approach 1:
The patent divides the complex 3D tooth image generation process into separate neural network modules: a first neural network processes cross-sectional images to generate intermediate representations, and a second neural network stacks these to create final 3D tooth images. This segmentation allows each network to specialize in specific processing tasks, improving overall computational efficiency and throughput.
Solution Approach 2:
The patent pre-processes dental cross-sectional images by dividing and organizing them before feeding them to the neural networks. The system prepares training data in advance with proper formatting and segmentation, which reduces the computational burden during actual 3D tooth image generation and accelerates processing throughput during clinical use.
3Measurement precision
If three-dimensional tooth images are generated using neural networks to eliminate metal artifacts, then tooth number detection accuracy improves, but loading time increases
Solution Approach 1:
The patent uses neural networks to create simplified 3D tooth images that copy only the essential tooth structures and spatial relationships, excluding metal crown artifacts. These synthesized 3D tooth images serve as accurate representations for tooth number identification without containing the interfering metal artifact data present in original CBCT scans.
Data Source
AI summary
A three-dimensional tooth image display apparatus, according to an embodiment of the present invention, comprises: a tooth division unit which divides a boundary of each object in a dental cross-section image generated by dividing an input three-dimensional dental image in an axial direction; a tooth detection unit which recognizes a tooth area among objects in the dental cross-sectional image and detects a tooth number of each tooth belonging to the tooth area; and a tooth image obtainment unit which generates a three-dimensional image of each tooth on the basis of the boundary of each object in each dental cross-sectional image and the tooth number of each tooth, which are obtained through the tooth division unit and the tooth detection unit, wherein the three-dimensional image of each tooth may have a different display method according to the tooth number.