Segmentation of Intra-Retinal Layers From Optical Coherence Tomography Images Using an Active Contour Approach

Abstract—Optical Coherence Tomography (OCT) is a noninvasive, depth-resolved imaging modality that has become a prominent ophthalmic diagnostic technique. We present a semiautomated segmentation algorithm to detect intra-retinal layers in OCT images acquired from rodent models of retinal degeneration. We adapt Chan–Vese’s energy-minimizing active contours without edges for the OCT images, which suffer from low contrast and are highly corrupted by noise. A multi-phase framework with a circular shape prior is adopted in order to model the boundaries of retinal layers and estimate the shape parameters using least squares. We use a contextual scheme to balance the weight of different terms in the energy functional. The results from various synthetic experiments and segmentation results on OCT images of rats are presented, demonstrating the strength of our method to detect the desired retinal layers with sufficient accuracy even in the presence of intensity inhomogeneity resulting fr...

• Type: Journal
• Year: 2011
• Where: TMI
• Authors: Azadeh Yazdanpanah, Ghassan Hamarneh, Benjamin R. Smith, Marinko Sarunic
• Keywords: Abstract—Optical Coherence Tomography, OCT Images, Retinal Layers, TMI 2011