🦷 NaviCavi - Automated Dental Caries Detection |🔗Explore the App
NaviCavi is a dental caries detection solution developed by B.S. in Computer Science students at Our Lady of Fatima University as part of their Undergraduate Thesis project.This innovative web-based platform utilizes a Convolutional Neural Network (CNN) algorithm to automatically detect and segment dental caries in panoramic dental radiographs, accurately pinpointing areas of concern.
- Automatic Caries Detection: Utilizes a CNN algorithm to locate dental caries with precision.
- Tooth Type Detection: Identifies type of tooth where the dental caries are located.
- Saved Detection Results: Users can save results from the detection process for future reference.
- User-Friendly Interface: Straightforward navigation and usability.
- Bootstrap
- BulmaCSS
- Ultralytics YOLOv8
- Tensorflow
- Flask
- Jinja
- SQLAlchemy
- PostgreSQL
- Render
Developed by B.S. in Computer Science students at Our Lady of Fatima University College of Computer Studies - Quezon City Campus.
Jan Paul Miguel Alva
Ellaine Dela Cruz
Louis Philip Dela Cruz
Asher Frank Luna
This project is licensed under the MIT License.
This repository is a representation of our actual project repository, but it has been modified to remove sensitive information. The following items have been removed or modified:
- API keys and credentials
- Model files and data
- Some files are only examples and may not be functional
Please note that this repository is intended for demonstration purposes only and should not be used for production or deployment.