ABSTRACT
The new technology using a spectral domain optical coherence tomography (SDOCT) scanner helps to view fine details of the retina. Optical Coherence Tomography is a powerful non-contact type imaging modality used to image various aspects of biological tissues, such as structural information, blood flow, elastic parameters, change of polarization states, and molecular content. SDOCT makes use of a low coherence interferometer to generate two- or three-dimensional imaging of biological samples by obtaining high-resolution cross-sectional backscattering profiles. Segmentation, however, remains one of the most difficult and at the same time most commonly required steps in Optical Coherence Tomography image analysis. Level sets can be used for image segmentation by using image based features such as mean intensity, gradient, and edges in the governing differential equation. One of the primary and classical variational level set models was developed by Chan and Vese. An effective segmentation algorithm was designed by which is capable of segmenting total retina and retinal pigment epithelium drusen complex.
