Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification

Zhihong Hu; Gerard G. Medioni; Matthias Hernandez; Srinivas  R. Sadda

doi:10.1117/1.JMI.2.1.014501

12 January 2015 Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification

Zhihong Hu, Gerard G. Medioni, Matthias Hernandez, Srinivas R. Sadda

Author Affiliations +

Journal of Medical Imaging, Vol. 2, Issue 1, 014501 (January 2015). https://doi.org/10.1117/1.JMI.2.1.014501

Abstract

Geographic atrophy (GA) is a manifestation of the advanced or late stage of age-related macular degeneration (AMD). AMD is the leading cause of blindness in people over the age of 65 in the western world. The purpose of this study is to develop a fully automated supervised pixel classification approach for segmenting GA, including uni- and multifocal patches in fundus autofluorescene (FAF) images. The image features include region-wise intensity measures, gray-level co-occurrence matrix measures, and Gaussian filter banks. A k-nearest-neighbor pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. Sixteen randomly chosen FAF images were obtained from 16 subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by a certified image reading center grader. Eight-fold cross-validation is applied to evaluate the algorithm performance. The mean overlap ratio (OR), area correlation (Pearson’s r), accuracy (ACC), true positive rate (TPR), specificity (SPC), positive predictive value (PPV), and false discovery rate (FDR) between the algorithm- and manually defined GA regions are 0.72±0.03, 0.98±0.02, 0.94±0.00, 0.87±0.01, 0.96±0.01, 0.80±0.04, and 0.20±0.04, respectively.

Citation Download Citation

Zhihong Hu, Gerard G. Medioni, Matthias Hernandez, and Srinivas R. Sadda "Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification," Journal of Medical Imaging 2(1), 014501 (12 January 2015). https://doi.org/10.1117/1.JMI.2.1.014501

Published: 12 January 2015

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