Comprehensive eye evaluation algorithm

C. Agurto; S. Nemeth; G. Zamora; M. Vahtel; P. Soliz; S. Barriga

doi:10.1117/12.2217130

24 March 2016 Comprehensive eye evaluation algorithm

C. Agurto , S. Nemeth, G. Zamora, M. Vahtel, P. Soliz, S. Barriga

Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 978518 (2016) https://doi.org/10.1117/12.2217130
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

In recent years, several research groups have developed automatic algorithms to detect diabetic retinopathy (DR) in individuals with diabetes (DM), using digital retinal images. Studies have indicated that diabetics have 1.5 times the annual risk of developing primary open angle glaucoma (POAG) as do people without DM. Moreover, DM patients have 1.8 times the risk for age-related macular degeneration (AMD). Although numerous investigators are developing automatic DR detection algorithms, there have been few successful efforts to create an automatic algorithm that can detect other ocular diseases, such as POAG and AMD. Consequently, our aim in the current study was to develop a comprehensive eye evaluation algorithm that not only detects DR in retinal images, but also automatically identifies glaucoma suspects and AMD by integrating other personal medical information with the retinal features. The proposed system is fully automatic and provides the likelihood of each of the three eye disease. The system was evaluated in two datasets of 104 and 88 diabetic cases. For each eye, we used two non-mydriatic digital color fundus photographs (macula and optic disc centered) and, when available, information about age, duration of diabetes, cataracts, hypertension, gender, and laboratory data. Our results show that the combination of multimodal features can increase the AUC by up to 5%, 7%, and 8% in the detection of AMD, DR, and glaucoma respectively. Marked improvement was achieved when laboratory results were combined with retinal image features.

Citation Download Citation

C. Agurto , S. Nemeth, G. Zamora, M. Vahtel, P. Soliz, and S. Barriga "Comprehensive eye evaluation algorithm", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978518 (24 March 2016); https://doi.org/10.1117/12.2217130

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Eye

Algorithm development

Blood

Macula

Control systems

Feature extraction

Databases

Show All Keywords

Keywords/Phrases

Search In:

Publication Years