Development of a Method for Reconstructing Fundus Volume Data from Cross-sectional Images Scanned Radially with an OCT

Abstract

In medicine, detailed observations of a three-dimensional fundus shape is necessary for diagnosing eye diseases accurately and checking the treatment process. In the paper, we propose a method for reconstructing fundus volume data accurately taking into account a fundus shape from cross-sectional images scanned radially with an optical coherence tomography (OCT). The method determines the position of cross-sectional images with a genetic algorithm and interpolates volume data from the cross-sectional images with displacement vectors. The fundus shape and its internal structures can be easily observed using the proposed method. The method is a promising technique for the diagnosis of glaucoma.