Optical coherence tomography scans were acquired using a Cirrus High Density SD-OCT (Carl Zeiss Meditec, Dublin, CA, USA), producing a 2 × 6 × 6-mm image cube (200 slices) around the optic nerve head. Automated quantitation of NPL from OCT images was performed in four steps: (1) identification of the inner limiting membrane (ILM), (2) generation of a three-dimensional (3D) surface, (3) smoothing, and (4) determination of baseline level. First, the depth of the ILM was detected from individual b-scans using thresholding. The identified anterior boundary from each b-scan was overlaid axially to form a 3D representation of the ILM. The resulting surface was smoothed using a median filter to remove speckle noise. Finally, a reference baseline level needed for determining the length of the protrusion was identified. Two different reference levels were tested. The first uses a low order polynomial curve fit of the ILM excluding the region of nerve protrusion (R1) and the second uses the RPE level (R2), resulting in two separate calculations of NPL, NPL-OCTR1, and NPL-OCTR2, respectively. In each case, NPL was then defined as the maximum height of the 3D surface relative to the reference level.