Dental Plaque Detection via Tooth Location Probability
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Solution Overview
Problem
Existing dental plaque detection systems using image analysis, such as QLF imaging, struggle to accurately distinguish between plaque and tartar, as both can produce high fluorescence signals, leading to incorrect feedback for users.
Innovation Solution
A system that integrates a camera and processor to analyze intra-oral images, detect image characteristics indicative of plaque and tartar, and estimate the likelihood of plaque presence based on tooth location, thereby improving discrimination between actionable plaque and unactionable tartar.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If QLF imaging is used to detect plaque, then plaque detection capability is improved, but discrimination between plaque and tartar deteriorates because both produce high fluorescence signals
Solution Approach 1:
The patent applies local quality by associating different probabilities with different tooth locations. The system divides the oral cavity into multiple tooth locations and assigns location-specific probabilities for plaque versus tartar presence. This allows the same fluorescence signal to be interpreted differently based on its location, thereby improving discrimination accuracy while maintaining detection sensitivity.
2Measurement precision
If fluorescence signal intensity is used as the sole indicator, then detection sensitivity is improved, but false positive rate increases due to inability to distinguish plaque from tartar
Solution Approach 1:
The patent changes the interpretation parameter by introducing location-based conditional probabilities. Instead of using a fixed threshold for fluorescence signal intensity, the system dynamically adjusts the interpretation of the signal based on the tooth location where it was detected. This transforms the detection criterion from a simple intensity threshold to a context-dependent probability assessment, reducing false positives while maintaining sensitivity.
3Device complexity
If simple QLF camera is used for detection, then device complexity is reduced, but ability to provide actionable feedback deteriorates due to lack of discrimination between plaque and tartar
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing probability values for plaque versus tartar presence at each tooth location. These probabilities are determined in advance based on dental knowledge and clinical data. During operation, the system simply retrieves the appropriate probability for the detected location and applies it to the fluorescence signal, enabling sophisticated discrimination without adding hardware complexity.
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
The system provides accurate plaque detection by leveraging tooth location as a prior for conditional probability, reducing false positives for tartar and enabling effective brushing guidance for users.
Implementation Method 1
blue light may be used to illuminate the teeth for QLF imaging. This causes the teeth to fluoresce in green (autofluorescence), whereas red fluorescence is caused as a result of the metabolic process of specific bacterial strains.
Data Source
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AI summary
A system and method are provided for detecting dental plaque. Intra-oral images are analyzed to detect image characteristics indicative of at least plaque and tartar. Tooth locations are detected at which the image characteristics are present; and a likelihood of plaque being present is derived based on the detected image characteristics and their associated tooth locations.