title: Semi-automatic geographic atrophy segmentation for SD-OCT images.
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.
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ; Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Chen
authors.affiliation: Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA.
authors.forename: Luis
authors.initials: L
authors.lastname: de Sisternes
authors.affiliation: Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, CA 94303, USA.
authors.forename: Theodore
authors.initials: T
authors.lastname: Leng
authors.affiliation: Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, CA 94303, USA.
authors.forename: Luoluo
authors.initials: L
authors.lastname: Zheng
authors.affiliation: Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, CA 94303, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: Kutzscher
authors.affiliation: Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA ; dlrubin@standford.edu.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Rubin
keywords: (100.0100) Image processing; (110.4500) Optical coherence tomography; (170.4470) Ophthalmology