Eye Disease Detection System

Project Title

Eye Disease Detection System

Project Area of Specialization Artificial IntelligenceProject Summary

Eye blindness is one of the major health problems that has adversely affected the population globally. Blindness is most often caused by a group of diseases such as cataracts, keratoconus, etc. Classical diagnosis requires expert ophthalmologists and suffers from intra-observer variability and subjectivity. Thus, there is a need for an automated system that can assist ophthalmologists in decision-making. The project’s main emphasis is on the detection of eye diseases, given that eye, is a very sensitive yet complex optical system and is subject to many diseases such as amblyopia, keratoconus, and many more to which there is no cure at present. As if right now the best possible option is to have these diseases treated immediately to halt their further progression. For the detection of such diseases, this project would include both research and development and would be conducted in the domain of deep learning and web application. The goal is to produce such a tool that will assist doctors. It will also help Technology experts, to extend this wort or other eye-related diseases.

Project Objectives

To create an assisting tool for the doctors for detection and IT experts to further extend its work.
 We aim for this tool to aid professionals in a very befitting way and contribute to the suffering community.
Finally, this project would be a great learning experience for us regarding Machine learning, model training, and Web development and open new paths for solving real-world health issues.

Project Implementation Method

We have proposed to make a web application integrated with a disease detection system trained using a convocational neural network to perform image recognition and image processing on the images gathered. Our top priority for detection will be employing corneal segmentation. For this approach, we would require datasets of the eyes that are affected to train the model. The final product will be an app that professionals and laymen can use for their convenience.

Benefits of the Project

The benefits behind this project is that cataracts is very prevalent and there has not been done much work in this domain. The project would be accepted widely as it is something that would assist the doctors and help reduce the probability of them making a human error. If the diseases are overlooked and left undiagnosed, it can affect the eye permanently. This project would a great learning exercise and expose us to the knowledge we are unaware of as we would apply all the knowledge gathered by us in this program to solve this real-life problem. Furthermore, there is a humanitarian inspiration behind this project as many people around us suffer form cataracts.

Technical Details of Final Deliverable

The final delieverable would be a web application integrated with a disease detection system trained using a convocational neural network to perform image recognition and image processing on the images gathered. Our top priority for detection will be employing corneal segmentation.  The final product will be an app that professionals and laymen can use for their convenience in real life situations. As machine learning has been used in the detection of other health issues, it can be applied to solve this issue as well.

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Medical Core Technology Artificial Intelligence(AI)Other TechnologiesSustainable 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)	70000
28D Lens	Equipment	1	70000	70000