Segmentation of 830 nm and 1310 nm lasik corneal optical coherence tomography images

Optical coherence tomography (OCT) provides a non-contact and non-invasive means to visualize the corneal anatomy at micron scale resolution. We obtained corneal images from an arc-scanning (converging) OCT system operating at a wavelength of 830 nm and a fan-shaped-scanning high-speed OCT system with an operating wavelength of 1310 nm. Different scan protocols (arc/fan) and data acquisition rates, as well as wavelength dependent bio-tissue backscatter contrast and optical absorption, make the images acquired using the two systems different. We developed image-processing algorithms to automatically detect the air-tear interface, epithelium-Bowman's layer interface, laser in-situ keratomileusis (LASIK) flap interface, and the cornea-aqueous interface in both kinds of images. The overall segmentation scheme for 830 nm and 1310 nm OCT images was similar, although different strategies were adopted for specific processing approaches. Ultrasound pachymetry measurements of the corneal thickness and Placido-ring based corneal topography measurements of the corneal curvature were made on the same day as the OCT examination. Anterior/posterior corneal surface curvature measurement with OCT was also investigated. Results showed that automated segmentation of OCT images could evaluate anatomic outcome of LASIK surgery.