A method for detection of retinal layers by optical coherence tomography image segmentation
A novel algorithm is reported for automatically segmenting optical coherence tomography (OCT) images to identify six layers within the retina. The boundary detection technique presented here is based on a 2-D edge detection scheme, in which a filter with wedge-shaped pass band is introduced. The proposed filter enhances edges along the vertical boundaries while suppressing speckle noise. The detected contours are labeled based on a retina model. The layer thickness measurements derived by the algorithm are compared with thickness measurements from manually marked boundaries. The automated thickness measurements derived by the algorithm differ from manual segmentation results by less than 5 microns on average.