Improving Oral Health Through Al-Driven SelfAssessment

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Healthteach USA
About Client

A leading HealthTech startup in the United States partnered with Imenso Software to make preventive dental care more accessible. The vision was a mobile-first app that lets people scan their teeth using a smartphone camera and receive near real-time oral-health insights—especially useful where dental visits are costly or hard to access.

Key Challenges

Accurate detection from consumer-grade selfies

Unlike clinical photographs taken under controlled lighting or intra-oral instruments, the app had to work reliably using smartphone front or rear cameras, variable lighting, differing mouth positions and angles, and on older iOS devices.

Teeth and gum segmentation in heterogeneous real-world conditions

Identifying teeth, gums, and relevant dental zones (e.g., lower molars, front incisors) purely from a self-taken image, and doing so robustly across tooth-shape variations, crowding or spacing, required strong computer-vision models.

Maintaining diagnostic precision without clinical tools

The system needed to emulate the insight of a dentist’s visual exam (detecting signs like enamel erosion, plaque film, gum inflammation, misalignment) while operating purely from a smartphone image.

Balancing interpretability and simplicity

The output of the AI had to be delivered in non-technical language so everyday users could understand their oral health status, get actionable advice and feel comfortable with the result. The challenge was translating clinical metrics into consumer-friendly guidance.

Resource-constrained performance and false-positive control

The app had to perform smoothly (especially on older phones), with limited compute, minimal lag, and low battery/thermal impact. At the same time, it needed to minimise false positives (unnecessary alerts) that might reduce user trust.

Key Challenges

Unlike clinical photographs taken under controlled lighting or intra-oral instruments, the app had to work reliably using smartphone front or rear cameras, variable lighting, differing mouth positions and angles, and on older iOS devices.

Identifying teeth, gums, and relevant dental zones (e.g., lower molars, front incisors) purely from a self-taken image, and doing so robustly across tooth-shape variations, crowding or spacing, required strong computer-vision models.

The system needed to emulate the insight of a dentist’s visual exam (detecting signs like enamel erosion, plaque film, gum inflammation, misalignment) while operating purely from a smartphone image.

The output of the AI had to be delivered in non-technical language so everyday users could understand their oral health status, get actionable advice and feel comfortable with the result. The challenge was translating clinical metrics into consumer-friendly guidance.

The app had to perform smoothly (especially on older phones), with limited compute, minimal lag, and low battery/thermal impact. At the same time, it needed to minimise false positives (unnecessary alerts) that might reduce user trust.

Solution
1

AI-Powered Oral Health Analysis

2

Secure Cloud Processing System

3

Testing, Validation & Optimization

Solution
1

AI-Powered Oral Health Analysis

Guided Selfie Image Capture

The native iOS application walks users through a structured selfie-capture process, ensuring proper framing, lighting, and image clarity. On-device pre-processing such as cropping, stabilization, and contrast correction improves image quality before analysis.

Intelligent Dental Condition Detection

Using Python, OpenCV, and CNN-based models, the system detects plaque, cavity risks, gum inflammation, tooth alignment issues, and enamel discoloration. The AI generates a comprehensive oral-health score while maintaining fast and reliable performance across devices.

2

Secure Cloud Processing System

Scalable Backend Infrastructure

Firebase services were used to manage authentication, image uploads, cloud storage, and AI-processing workflows securely. The architecture supports high-volume user activity while maintaining strong performance and data protection standards.

Real-Time Health Reporting

Users receive easy-to-understand oral-health reports containing detected issues, oral-health scores, and actionable next steps. The platform also provides personalized brushing tips, flossing recommendations, and preventive care guidance.

3

Testing, Validation & Optimization

Cross-Device Performance Testing

Extensive testing across multiple iPhone models and varying lighting conditions ensured stable app performance and minimized false positives. Continuous optimization improved inference speed, usability, and overall user experience.

Continuous AI Model Improvement

Clinical validation compared AI-generated results with dentist assessments, achieving strong accuracy for key indicators. The modular system supports ongoing retraining, analytics-based monitoring, and future expansion to additional platforms like Android.

Tech Stack

Outcome Summary

68%

68% of users discovered risks they didn’t know about—driving awareness and early action.

6.2-minute

Average 6.2-minute sessions due to personalized guidance and clear results.

92%

92% AI accuracy when compared to dentists’ visual evaluations of key oral indicators

Conclusion

Imenso Software transformed a strong idea into a practical preventive-care tool. By combining AI accuracy with iOS experience and lightweight cloud services, the app helps everyday users understand their oral health quickly and act earlier—without replacing formal dental care when it’s needed.

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