Share Email Print

Proceedings Paper

Longitudinal graph-based segmentation of macular OCT using fundus alignment
Author(s): Andrew Lang; Aaron Carass; Omar Al-Louzi; Pavan Bhargava; Howard S. Ying; Peter A. Calabresi; Jerry L. Prince
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Segmentation of retinal layers in optical coherence tomography (OCT) has become an important diagnostic tool for a variety of ocular and neurological diseases. Currently all OCT segmentation algorithms analyze data independently, ignoring previous scans, which can lead to spurious measurements due to algorithm variability and failure to identify subtle changes in retinal layers. In this paper, we present a graph-based segmentation framework to provide consistent longitudinal segmentation results. Regularization over time is accomplished by adding weighted edges between corresponding voxels at each visit. We align the scans to a common subject space before connecting the graphs by registering the data using both the retinal vasculature and retinal thickness generated from a low resolution segmentation. This initial segmentation also allows the higher dimensional temporal problem to be solved more efficiently by reducing the graph size. Validation is performed on longitudinal data from 24 subjects, where we explore the variability between our longitudinal graph method and a cross-sectional graph approach. Our results demonstrate that the longitudinal component improves segmentation consistency, particularly in areas where the boundaries are difficult to visualize due to poor scan quality.

Paper Details

Date Published: 20 March 2015
PDF: 8 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94130M (20 March 2015); doi: 10.1117/12.2077713
Show Author Affiliations
Andrew Lang, Johns Hopkins Univ. (United States)
Aaron Carass, Johns Hopkins Univ. (United States)
Omar Al-Louzi, Johns Hopkins Univ. School of Medicine (United States)
Pavan Bhargava, Johns Hopkins Univ. School of Medicine (United States)
Howard S. Ying, Johns Hopkins Univ. School of Medicine (United States)
Peter A. Calabresi, Johns Hopkins Univ. School of Medicine (United States)
Jerry L. Prince, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?