Share Email Print

Proceedings Paper

Automated method for RNFL segmentation in spectral domain OCT
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We introduce a method based on optical reflectivity changes to segment the retinal nerve fiber layer (RNFL) in images recorded using swept source spectral domain optical coherence tomography (OCT). The segmented image is used to determine the RNFL thickness. Simple filtering followed by edge detecting techniques can successfully be applied to segment the RNFL from recorded images and estimate RNFL thickness. The method is computationally more efficient than previously reported approaches. Higher computational efficiency allows faster segmentation and provides the ophthalmologist segmented retinal images that better utilize advantages of spectral domain OCT instrumentation. OCT B-scan and fundus images of the retina are recorded for 5 patients. The segmentation method is applied on B-scan images recorded from all patients. An expert ophthalmologist separately demarcates the RNFL layer in the OCT images from the same patients in each B-scan image. Results from automated image processing software are compared to the boundary demarcated by the expert ophthalmologist. The absolute error between the boundaries demarcated by the expert and the algorithm is expressed in terms of area and is used as an error metric. Ability of the algorithm to accurately segment the RNFL in comparison with an expert ophthalmologist is reported.

Paper Details

Date Published: 12 February 2008
PDF: 9 pages
Proc. SPIE 6848, Advanced Biomedical and Clinical Diagnostic Systems VI, 68480N (12 February 2008); doi: 10.1117/12.763491
Show Author Affiliations
Amit S. Paranjape, Univ. of Texas at Austin (United States)
Badr Elmaanaoui, Univ. of Texas at Austin (United States)
Jordan Dewelle, Univ. of Texas at Austin (United States)
H. Grady Rylander, Univ. of Texas at Austin (United States)
Thomas E. Milner, Univ. of Texas at Austin (United States)

Published in SPIE Proceedings Vol. 6848:
Advanced Biomedical and Clinical Diagnostic Systems VI
Tuan Vo-Dinh; Warren S. Grundfest; David A. Benaron; Gerald E. Cohn, Editor(s)

© SPIE. Terms of Use
Back to Top