Iris imaging for health diagnostics

The development of mobile technology and machine learning tools has made it easier than ever to monitor health without visiting a doctor. In this thesis, we explore the use of iris imaging as a medical diagnostic tool. We implement a system in which images captured using a mobile device can be uploaded to and analyzed by a central server. With this platform, we hope to build a large database of standard iris images with labeled medical data and facilitate studies of iris diagnostics. In our implementation, the feature extraction and classification tools built are applied to predict diabetes, through a study conducted in collaboration with researchers at Swami Vivekananda Yoga Anusandhana Samsthana (SVYASA). The results show improvement in prediction accuracy and encourage further development of the server platform for future, large-scale studies.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Yu, Tania Weidan

Advisor dc:contributor.advisor

• Richard Fletcher.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/119548

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/119548