Dental Cavity Detection

Project Title

Dental Cavity Detection

Project Area of Specialization Artificial IntelligenceProject Summary

The dependency of technology on Digital Image Processing (DIP) and Artificial Intelligence (AI) is not new but more recently, AI emerges to be the essential component not only related to science and technology but in every field that human life touches or depends.

The core concept of our project is to develop a system to aid dentists to determine the dental cavity, if occurs, by processing the dental X-Ray image of human jaw to highlight the essential features and send it to the developed AI engine to determine the position of the cavity.

The major advantages of our developed system are to ease the burden of manual processing of cavity determination and also it is not intrusive for patients having such cavities.

In this project, dental image X-Ray is analyzed using image processing and AI techniques and detect the cavity, if present, in the image. 

Project Objectives

Following are the key objectives of the project:

To develop an image processing module that processes the dental X-Ray image and as output effectively highlight the features of the human jaw so that essential feature points may be extracted for further analysis.

To develop an AI based machine learning module that is used to train the extracted feature points from the dental X-Ray image. A large set of these feature points are used for enhanced learning of the system.

To integrate these modules into a single system so that any dental X-Ray image of the jaw can be given as input, processed and provides the essential information about the presence and location of the cavity, if any.

This is a Research based project, and the main objective of this project is to implement the concepts of Digital Image Processing and Machine Learning in the field of dentistry and medical science.

Project Implementation Method

In the project, the system is installed on Raspberry Pi using Python and OpenCV. The dental X-Ray image is fed to the image processing module that processes the image to highlight the feature points which are essential for cavity determination. Once these feature points are calculated and highlighted, these points are then fed to AI module to determine the presence of cavity, if found. Additionally, these points are used to further train the system for continuous learning i.e. Machine Learning. The mode of learning in this project is supervised. The final output of the system is the highlighted boundary around the cavity, if found, or system provides the message of “no cavity detected”.

Benefits of the Project

1. Not intrusive at all.
2. Extremely easy to use even by a person with a little knowledge about computing.
3. System is portable.
4. Cavities can easily be detected.
5. No need to visit a dentist at initial level, dental X-Rays would be enough to find cavities.
6. Less chances of human error.
7. Would be beneficial for future research work and would open many doors for further research in medical imaging and analysis.

Technical Details of Final Deliverable

A Raspberry Pi based system using Python and OpenCV as the platform for the developed application. The application is equipped with Digital Image Processing module as well as Artificial Intelligence based learning module for effective localization of dental cavity.

Final Deliverable of the Project Hardware SystemCore Industry MedicalOther Industries Medical , Health Core Technology Artificial Intelligence(AI)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	34800
Raspberry Pi 4 B	Equipment	1	15000	15000
LCD Screen	Equipment	1	10000	10000
Keyboard and Mouse	Equipment	1	2000	2000
Raspberry Pi Power Supply	Equipment	1	1000	1000
32GB Memory Card	Equipment	1	2000	2000
VGA Cable	Equipment	1	400	400
HDMI to VGA Converter	Equipment	1	400	400
Documentation	Miscellaneous	2	2000	4000