Automated segmentation of neural canal opening and optic cup in 3D spectral optical coherence tomography volumes of the optic nerve head

Abstract

Purpose: To develop an automated approach for segmenting the neural canal opening (NCO) and cup at the level of the retinal pigment epithelium (RPE)/Bruch's membrane (BM) complex in spectral-domain optical coherence tomography (SD-OCT) volumes. To investigate the correspondence and discrepancy between the NCO-based metrics and the clinical disc margin on fundus photographs of glaucoma subjects.

Methods: SD-OCT scans and corresponding stereo fundus photographs of the optic nerve head were obtained from 68 eyes of 34 patients with glaucoma or glaucoma suspicion. Manual planimetry was performed by three glaucoma experts to delineate a reference standard (RS) for cup and disc margins from the images. An automated graph-theoretic approach was used to identify the NCO and cup. NCO-based metrics were compared with the RS.

Results: Compared with the RS disc margin, the authors found mean unsigned and signed border differences of 2.81 ± 1.48 pixels (0.084 ± 0.044 mm) and -0.99 ± 2.02 pixels (-0.030 ± 0.061 mm), respectively, for NCO segmentation. The correlations of the linear cup-to-disc (NCO) area ratio, disc (NCO) area, rim area, and cup area of the algorithm with the RS were 0.85, 0.77, 0.69, and 0.83, respectively.

Conclusions: In most eyes, the NCO-based 2D metrics, as estimated by the novel automated graph-theoretic approach to segment the NCO and cup at the level of the RPE/BM complex in SD-OCT volumes, correlate well with RS. However, a small discrepancy exists in NCO-based anatomic structures and the clinical disc margin of the RS in some eyes.

Figure 1.

Illustration of SD-OCT volume flattening. (a) Central slice from the original raw SD-OCT. (b) Four surface segmentations of the original raw volume. (c) 3D rendering of the surface segmentation by mapping of the projection image texture onto the top surface. (d) Central slice from the flattened SD-OCT. (e) Four surface segmentations of the flattened volume. (f) 3D rendering of the surface segmentation of the flattened volume by mapping the projection image texture onto the top surface.

Figure 2.

Illustration of the NCO and optic cup segmentation at the RPE/BM plane. (a) Planar surfaces near RPE/BM complex. (b) Projection image. (c) Segmented boundaries overlapping with the unwrapped cost image. (d, e) Segmented NCO and cup overlapping with (d) projection image and (e) cross-sectional slice of OCT volume. (f) 3D rendering of the NCO and cup segmentation overlapping with the mapping of the projection image texture onto the top surface.

Figure 3.

Scatterplots of the NCO, rim, and cup area at the RPE/BM plane from the algorithm to the disc, rim, and cup area from RS for the 68 eyes. Diagonal line: perfect correlation of 1.0.

Figure 4.

Scatterplots of linear cup-to-NCO of algorithm to LCDR of RS for 68 eyes. Diagonal line: perfect correlation of 1.0.

Figure 5.

Random selection of example NCO segmentations. (A) Projection image. (B) Corresponding fundus image. (C, D) NCO and cup at RPE/BM plane from present algorithm and disc and cup from RS transposed to projection image, respectively. (E, F) NCO and cup at RPE/BM plane from present algorithm and disc and cup from RS transposed to fundus image, respectively.

Figure 6.

Comparison of present algorithm, expert, and previous algorithm segmentations with a good match. Raw SD-OCT and corresponding fundus image (row 1), present algorithm (row 2), RS (row 3), and previous algorithm (row 4) segmentations overlapping with raw SD-OCT and corresponding fundus image. SD-OCT central B-scan (left) and fundus image (right). Yellow arrows: position of the NCO from the algorithm (dashed yellow line indicates the projected NCO position). Blue arrows: clinical disc from the RS. Green, red: each method's projected rim and cup regions, respectively.

Figure 7.

Comparison of present algorithm, expert, and previous algorithm segmentations with discrepancy. Raw SD-OCT and corresponding fundus image (row 1), present algorithm (row 2), RS (row 3), and previous algorithm (row 4) segmentations overlapping with raw SD-OCT and corresponding fundus image. SD-OCT central B-scan (left). Fundus image (right). Yellow arrows: position of the NCO from the algorithm (dashed yellow line indicates the projected NCO position). Blue arrows: clinical disc from the RS. Green, red: each method's projected rim and cup regions, respectively.

Figure 8.

Comparison of present algorithm, expert, and previous algorithm segmentations with discrepancy. Raw SD-OCT and corresponding fundus image (row 1), present algorithm (row 2), RS (row 3), and previous algorithm (row 4) segmentations overlapping with raw SD-OCT and corresponding fundus image. SD-OCT central B-scan (left). Fundus image (right). Yellow arrows: position of the NCO from the algorithm (dashed yellow line indicates the projected NCO position). Blue arrows: clinical disc from the RS. Green, red: each method's projected rim and cup regions, respectively.