Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease.

ABSTRACT: In macular spectral domain optical coherence tomography (SD-OCT) volumes, detection of the foveal center is required for accurate and reproducible follow-up studies, structure function correlation, and measurement grid positioning. However, disease can cause severe obscuring or deformation of the fovea, thus presenting a major challenge in automated detection. We propose a fully automated fovea detection algorithm to extract the fovea position in SD-OCT volumes of eyes with exudative maculopathy. The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. Based on foveal type classification, the fovea position is computed based on retinal nerve fiber layer thickness. Mean absolute distance between system and clinical exp

SUBMITTER: Wu J 

PROVIDER: S-EPMC5021903 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature