Multi-Modal Dental Imaging for Caries Detection
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Solution Overview
Problem
Current dental caries detection methods, including fluorescence imaging, face challenges in accurately identifying incipient caries due to low image contrast and the need for manual extraction of lesion regions, which is time-consuming and subjective, and lack comprehensive assessment of caries and other tooth conditions like plaque and calculus.
Innovation Solution
A method that combines reflectance and fluorescence image data to enhance image contrast, using multi-modal image registration and feature vectors to automatically detect and quantify caries, plaque, and calculus, providing improved visualization and aiding practitioners in treatment planning and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If fluorescence imaging is used for caries detection, then non-invasive imaging is achieved, but image contrast between healthy and infected areas is poor
Solution Approach 1:
The patent combines reflectance imaging and fluorescence imaging into a multi-modal imaging system. The reflectance component provides structural information and contrast, while the fluorescence component provides functional information about bacterial activity and demineralization. By merging these two imaging modalities, the system achieves both non-invasive imaging and improved image contrast for accurate caries detection.
2Measurement precision
If manual extraction of lesion regions is used, then detection can be performed, but it is time-consuming and subjective
Solution Approach 1:
The patent implements automated lesion region extraction using image processing algorithms that automatically identify and segment carious areas from the multi-modal images. The system uses feature extraction and classification algorithms to detect lesion boundaries and characteristics without manual intervention, making the detection process both faster and more objective while maintaining high accuracy.
3Device complexity
If single-modal imaging is used, then device complexity is low, but comprehensive assessment of tooth conditions is limited
Solution Approach 1:
The patent creates a multi-functional imaging system that can assess multiple tooth conditions including caries, plaque, and calculus simultaneously. The system uses dual excitation light sources (blue and red) and multiple detection channels to capture reflectance and fluorescence signals, enabling comprehensive assessment of various dental conditions with a single integrated device rather than requiring separate specialized instruments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and early detection of caries, reduces manual extraction time, and provides comprehensive assessment of dental conditions, improving diagnostic accuracy and treatment effectiveness.
Implementation Method 1
This technique, sometimes termed quantitative light-induced fluorescence (QLF), operates on the principle that sound, healthy tooth enamel yields a higher intensity of fluorescence under excitation from some wavelengths than does de-mineralized enamel that has been damaged by caries infection. A different relationship has been found for red light excitation, a region of the spectrum for which bacteria and bacterial by-products in carious regions absorb and fluoresce more pronouncedly than do healthy areas.
Data Source
AI summary
A system and method for imaging a tooth. The method illuminates the tooth and acquires reflectance image data and illuminates the tooth and acquires fluorescence image data from the tooth. The acquired reflectance and fluorescence image data for the tooth are aligned to form aligned reflectance and fluorescence image data. For one or more pixels of the aligned reflectance and fluorescence image data, at least one feature vector is generated, having data derived from one or both of the aligned reflectance and fluorescence image data. The aligned reflectance and fluorescence image data and the at least one feature vector are processed using one or more trained classifiers obtained from a memory that is in signal communication with the computer. Processing results indicative of tooth condition are displayed.