OSA's Digital Library

Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 12 — Dec. 1, 2013
  • pp: 2729–2750

Semi-automatic geographic atrophy segmentation for SD-OCT images

Qiang Chen, Luis de Sisternes, Theodore Leng, Luoluo Zheng, Lauren Kutzscher, and Daniel L. Rubin  »View Author Affiliations


Biomedical Optics Express, Vol. 4, Issue 12, pp. 2729-2750 (2013)
http://dx.doi.org/10.1364/BOE.4.002729


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Abstract

Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography (SD-OCT) images. The method first identifies and segments a surface between the RPE and the choroid to generate retinal projection images in which the projection region is restricted to a sub-volume of the retina where the presence of GA can be identified. Subsequently, a geometric active contour model is employed to automatically detect and segment the extent of GA in the projection images. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to qualitatively and quantitatively evaluate the proposed GA segmentation method. Experimental results suggest that the proposed algorithm can achieve high segmentation accuracy. The mean GA overlap ratios between our proposed method and outlines drawn in the SD-OCT scans, our method and outlines drawn in the fundus auto-fluorescence (FAF) images, and the commercial software (Carl Zeiss Meditec proprietary software, Cirrus version 6.0) and outlines drawn in FAF images were 72.60%, 65.88% and 59.83%, respectively.

© 2013 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(110.4500) Imaging systems : Optical coherence tomography
(170.4470) Medical optics and biotechnology : Ophthalmology

ToC Category:
Image Processing

History
Original Manuscript: August 16, 2013
Revised Manuscript: October 17, 2013
Manuscript Accepted: October 19, 2013
Published: November 1, 2013

Citation
Qiang Chen, Luis de Sisternes, Theodore Leng, Luoluo Zheng, Lauren Kutzscher, and Daniel L. Rubin, "Semi-automatic geographic atrophy segmentation for SD-OCT images," Biomed. Opt. Express 4, 2729-2750 (2013)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-4-12-2729


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