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Abstract #65808 Published in IGR 17-3
Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
Wu M; Leng T; de Sisternes L; Rubin DL; Chen QOptics express 2015; 23: 31216-31229
Glaucoma is one of the most common causes of blindness worldwide. Early detection of glaucoma is traditionally based on assessment of the cup-to-disc (C/D) ratio, an important indicator of structural changes to the optic nerve head. Here, we present an automated optic disc segmentation algorithm in 3-D spectral domain optical coherence tomography (SD-OCT) volumes to quantify this ratio. The proposed algorithm utilizes a two-stage strategy. First, it detects the neural canal opening (NCO) by finding the points with maximum curvature on the retinal pigment epithelium (RPE) boundary with a spatial correlation smoothness constraint on consecutive B-scans, and it approximately locates the coarse disc margin in the projection image using convex hull fitting. Then, a patch searching procedure using a probabilistic support vector machine (SVM) classifier finds the most likely patch with the NCO in its center in order to refine the segmentation result. Thus, a reference plane can be determined to calculate the C/D radio. Experimental results on 42 SD-OCT volumes from 17 glaucoma patients demonstrate that the proposed algorithm can achieve high segmentation accuracy and a low C/D ratio evaluation error. The unsigned border error for optic disc segmentation and the evaluation error for C/D ratio comparing with manual segmentation are 2.216 ± 1.406 pixels (0.067 ± 0.042 mm) and 0.045 ± 0.033, respectively.
Classification:
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
6.9.2.2 Posterior (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis > 6.9.2 Optical coherence tomography)
