FurcaVision

Our AI-powered web app detects furcation defects and bone loss in dental X-rays, providing fast, accurate, and accessible analysis to support early diagnosis and better patient care.

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Inspiration

Early detection of furcation defects is crucial in preventing advanced periodontal disease and tooth loss. However, identifying these defects in dental X-rays is time-consuming and requires expert analysis. We aimed to create an AI-powered solution that automates this process, making diagnostics faster and more accessible for dental professionals.

What It Does

FurcaVision automatically analyzes dental X-rays to detect furcation defects and bone loss. It:

  • Classifies images as "With Furcation" or "Without Furcation" using deep learning.
  • Extracts individual teeth for focused analysis.
  • Marks both furcation defect areas and bone loss regions for better visualization.

How We Built It

AI Model

We developed a multi-model deep learning system:

  • Teeth Extraction Model: Built on YOLOv8, it segments and extracts individual teeth from X-rays for precise analysis.
  • Furcation Marker Model: Uses U-Net with MobileNetV2 as the backbone to detect and highlight furcation defect areas.
  • Bone Loss Marker Model: Also based on U-Net with MobileNetV2, it identifies and marks bone loss regions in the X-rays.
  • Classification Model: A fine-tuned DenseNet201 classifies X-rays into "With Furcation" or "Without Furcation."

Tech Stack

  • Frontend: React with Chakra UI for a smooth and responsive user experience.
  • Backend: Node.js and Express, integrating TensorFlow for real-time predictions.
  • Deployment: Hosted on a web platform for easy accessibility without installation.

Challenges We Ran Into

  • Data Limitations: Finding and preprocessing a well-labeled dataset for furcation defects and bone loss was challenging.
  • Model Optimization: Balancing accuracy while ensuring real-time performance required extensive tuning.
  • Integration Issues: Coordinating multiple deep learning models to work seamlessly in a web-based system.

Accomplishments That We're Proud Of

  • Successfully developed a multi-model AI system for furcation detection and bone loss analysis.
  • Integrated deep learning models into a fully functional web application.
  • Created a user-friendly interface that simplifies dental diagnostics for professionals.

What We Learned

  • Implementing multiple AI models requires careful coordination and optimization.
  • Medical imaging analysis demands high-quality datasets and robust preprocessing.
  • Efficient model deployment is crucial for a smooth user experience in web-based AI applications.

What's Next for FurcaVision – AI-Powered Furcation Detection

  • Enhanced Accuracy: Further refining models with larger, high-quality datasets.
  • Additional Dental Diagnostics: Expanding beyond furcation defects to detect other periodontal issues.
  • User Feedback & Testing: Collaborating with dental professionals to improve usability.
  • Mobile Compatibility: Extending support for mobile devices for greater accessibility.

FurcaVision aims to revolutionize dental diagnostics by enabling early, accurate, and efficient detection of furcation defects and bone loss. 🚀

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