State-of-the-Art of Level-Set Methods in Segmentation and Registration of Spectral Domain Optical Coherence Tomographic Retinal Images

In the quantitative assessment of Diabetic maculopathy from Spectral Domain Optical Coherence Tomography (SDOCT) images, analysis of intraretinal fluid filled regions plays a vital role because of its comparative superiority in providing tissue-level anatomical information. The detailed study on efficacy and performance of soft computing techniques-based automatic detection and diagnosis for SDOCT retinal images is still in the preliminary stage. Although some automatic algorithms have been proposed to segment retinal layers in recent times, full accuracy in edge detection continues to be a challenging problem. Some researchers have developed different versions of automatic algorithms for segmenting intraretinal fluid based on region-based level-set method and the retinal layers by dual gradient method. This particular level-set implementation is carried out using a fast front propagation algorithm. A valid search region is then defined to identify layer boundaries. The features of ...