To evaluate the automated segmentation algorithm for detection of intra-retinal layers to process images obtained from ultra-high resolution optical coherence tomography(OCT). Graph theory and the shortest path search based on dynamic programming were applied to automatically segment the 8 intra-retinal layers. We experimentally verified the accuracy and reliability of the algorithm. The results showed that the intra-retinal layer boundaries between automated and manual segmentations matched well. The algorithm successfully segmented the intra-retinal layers in glaucoma, high myopia, and retinitis pigmentosa patients. The proposed automatic segmentation for intra-retinal layers provides a promising tool for quantitative analysis in clinical diagnosis and treatment.